Selectional Restrictions 1
Running Head: FRAME-BASED DESCRIPTION OF SELECTION
Selectional restrictions are based on semantic frames: A case
study of the Japanese verb osou
Keiko Nakamoto
Affiliation: Graduate School of Education, Kyoto University Address: Yoshida-Honmachi, Sakyo-ku, Kyoto 606-8501, Japan
Kow Kuroda
Affiliation: National Institute for Information, Communication and Technology Address: 3-5 Hikaridai, Seika-cho, Soraku-gun, Kyoto 619-0289, Japan
Hajime Nozawa
Affiliation: National Institute for Information, Communication and Technology Address: 3-5 Hikaridai, Seika-cho, Soraku-gun, Kyoto 619-0289, Japan
Takashi Kusumi
Affiliation: Graduate School of Education, Kyoto University Address: Yoshida-Honmachi, Sakyo-ku, Kyoto 606-8501, Japan
Contact: Keiko Nakamoto #302, Residence-Nishijin 21, 590 Tougorou-cho, Kamigyo-ku, Kyoto, 602-8254 Japan. TEL/FAX: +81-75-415-2626
E-mail: [email protected], [email protected]
Selectional Restrictions 2
Acknowledgments
The first and the second authors listed have contributed equally to this
paper. This research was partly supported by the 21st Century COE Program (D-2,
Kyoto University) of the Ministry of Education, Culture, Sports, Science and
Technology, Japan. The authors would like to thank Toshiyuki Kanamaru for the
materials used in the experiments. Correspondence concerning this paper should be
addressed to either Keiko Nakamoto, Department of Cognitive Psychology in
Education, Graduate School of Education, Kyoto University
([email protected]), or Kow Kuroda, Natural Language Processing Group,
National Institute for Information, Communication and Technology
Selectional Restrictions 3
Abstract
This study aims at proposing an empirical approach on the basis of Semantic
Frames in order to construct a representational model of selectional restrictions.
First, sentences containing the Japanese verb osou (which roughly translates into
attack) were manually analyzed by linguists. It was demonstrated that the
selectional restrictions of osou and the disambiguation of the verb were mutually
dependent, and that their meanings could be expressed as a form of situation-level
frames. Second, in the experiments,participants were required to choose as many
NPs as possible to fill the blank in sentence frames like “____ attacked the bank in
the capital city” (originally in Japanese). The results indicated that the contingency
patterns of the subject and the object NPs were completely consistent with the
prediction by the semantic frame analysis. These results suggest the need for an
appropriate theory linking linguistic expressions to semantic understanding.
Selectional Restrictions 4
Introduction
Selectional restrictions are well-known phenomena in linguistic and
psycholinguistic studies. However, they require explanation—neither empirical nor
theoretical studies have provided an overall picture that describes and explains
selectional restrictions (Resnik, 1994; Pustejovsky, 1995).
In general, traditional accounts of selectional restrictions implicitly
assumed that they are a set of constraints imposed by the verb, i.e., the head of a
sentence. More specifically, these approaches presumed that verb meanings are
directly tied to event knowledge, and consequently serve as an effective source of
semantic constraints in the interpretation of co-occurring words, especially if these
are their “arguments.” According to the most radical verb-based view, it is the verb
that conveys all the crucial information for sentence processing, including
information required for thematic role assignment. Many researchers are aware
that such a verb-centered view of semantics hardly agrees with real data; however,
most of the practical analyses and accounts for selectional restrictions made in
linguistics and related fields of research have not strayed very far from this view.
This is probably because it is a view long maintained due to its theoretical
compatibility with supposedly important general principles of grammar, such as the
(Extended) Projection Principle posited in Principles and Parameters Theory
(Chomsky, 1986), the Head Principle posited in Head-driven Phrase Structure
Grammar (HPSG) (Pollard & Sag, 1994) and so on. These are principles that
guarantee the principle of compositionality for semantics as well as syntax. If the
basic semantic properties of a sentence were not predicted from the properties of its
head, i.e., the verb, how can the interpretation of a given sentence be sound and
plausible? This is the question that most linguists have in mind.
Selectional Restrictions 5
Recently, however, several studies have shown that verb meaning alone is
insufficient to explain the set of phenomena related to selectional restrictions and
thematic role assignment (Altman, 1999; Kamide, Altman, & Haywood, 2003;
McRae, Hare, Elman, & Ferretti, in press; McRae, Hare, Ferretti, & Elman, 2001;
Vu, Kellas, Petersen, & Metcalf, 2003). For example, McRae et al. (in press) showed
that nouns evoke event knowledge and facilitate the processing of the following
related verb if they denote the agent, the patient involved in a specific event, or
even the location of the event. For example, the participants in their experiment
were able to name the verb performing faster when they saw it after the noun actor
than when they saw it after semantically unrelated nouns like waiter. In addition,
Kamide et al. (2003) revealed that the patient for a verb preferred by participants
varied as a function of the agent noun phrase (NP). In their eye-tracking
experiment, the participants looked more often at a picture of sweets when they
heard The girl will taste; on hearing The man will taste, they looked more often at a
picture of beer. These studies show that the role of nouns in selectional restrictions
is as important as that of verbs, and that the event knowledge evoked by nominal
items affects sentence processing in important ways.
While these are very insightful findings for understanding the mechanism
of sentence comprehension processes, it appears that an appropriate representation
model describing the relationship between linguistic expressions and the event
knowledge evoked by them remains elusive. For example, Ferretti et al. (2001)
suggested that verb meaning varies depending on what types of arguments it takes.
However, the question of how to “encode” the interrelationship among a given verb’s
meaning, co-occurrence restrictions on its arguments and modifiers, and event
knowledge evoked by any of these, was not entirely discussed.
Selectional Restrictions 6
As the above discussion suggests, it is of great importance to note that
knowledge of a particular event is evoked by a verb and its arguments for revealing
the relationship between linguistic expressions and event knowledge. As Kamide et
al. (2003) showed, while the verb taste requires for its object a noun phrase that
denotes an edible thing, what constitutes an edible thing depends on the type of its
subject, the agent of tasting: ants will be edible for anteaters but not for sharks. In
other words, even if verb meanings provide abstract, schematic representations of
actions or events, they would still not be sufficiently informative for imposing
realistic restrictions on the semantics of their arguments. Moreover, meanings of
verbs mutate quite easily, adapting to the “environments” that their arguments, in
part, comprise For instance, Gentner and France (1988) demonstrated that, when
presented a sentence in which a noun and a verb were semantically ill-matched (e.g.,
The lizard worshipped), people tended to alter, or “adjust,” the meaning of the verb
in order to make the sentence interpretable. Some readers might believe that
context-induced semantic mutation of verbs occurs only when people are presented
with a verb and noun pair that is extremely mismatched, and can therefore safely
be ignored as an exception. However, this is not the case: every verb always displays
a semantic change, no matter how subtle, as a result of its adaptation to a lexical
context. Consider the sentence A group of masked men attacked the bank. It clearly
implies that the robbers, “a group of masked men,” used violence (perhaps by using
guns) to attempt to steal money from the bank. In a very similar sentence, A group
of masked men attacked the military base, “a group of masked men” (if successful)
are understood to have aggressively occupied the base, perhaps for political reasons.
These informal observations suggest that verb meanings are highly
context-sensitive and even mutable. This implies that selectional restrictions are
Selectional Restrictions 7
not a phenomenon that would be properly treated as a lexical phenomenon; their
appropriate characterization would surpass any explanation that is based solely on
the semantics of a verb.
This suggests the need for developing a (desirably computational) model of
semantics that allows a description of the co-variational and co-compositional
semantics1, given a verb and co-occurring nouns. Such a semantics capable of
expressing semantic interdependency is precisely what is required for the
appropriate characterization of selectional restrictions.
Frame Semantics and its Extension
Clearly, it is difficult to coherently characterize selectional restrictions due
to co-variational nature of semantics. For this, we employed a theoretical approach
inspired by Frame Semantics (Fillmore, 1982, 1985) and Berkeley FrameNet
(Fillmore et. al., 2001, 2003). For illustration, we briefly present its basic tenets.
Frame Semantics (FS) is a linguistic theory proposed by Charles J. Fillmore.
Its aim is to provide a description of lexical meanings in terms of “semantic frames,”
a theoretical construct that has linkages to Marvin Minsky’s “frames” (Minksy,
1977).
FS posits that each word in a sentence “evokes” a particular semantic frame
and profiles some element or aspect of the frame. The integration of the evoked
frames constitutes the interpretation, or the “understood content,” of the sentence.
FS characterizes a semantic frame as a piece of worldknowledge that
represents or encodes a situation, scene, series of scenes, or an event comprising
these. It defines a semantic frame as an organization of a number of elements called
frame elements (FEs). FEs include event participants such as an Agent and a
Selectional Restrictions 8
Patient. Along with these basic participant class elements, other types of elements
are regarded as elements of a frame: the Manner in which a participant behaves,
the Reason and Purpose that of a participant, and the Time and Place at which an
event occurs.
Berkeley FrameNet (BFN) is an ongoing project that aims to provide a
large-scale database of semantic frames (for English) and annotated corpora, based
on the assumptions in FS. To build the database of frames, BFN collects lexical
items that evoke a particular frame, identifies them as “lexical units” (LUs) for that
frame, and provides a definition to the frame in terms of FS. To illustrate this, we
have provided the definition of the Attack frame below (Berkeley FrameNet project,
2005):
Attack
Definition:
An Assailant physically attacks a Victim (which is usually but not always
sentient), causing or intending to cause the Victim physical damage. A
Weapon used by the Assailant may also be mentioned, in addition to the
usual Place, Time, Purpose, Reason, etc. Sometimes, a location is used
metonymically to stand for the Assailant or the Victim, and in such cases,
the Place FE will be annotated on a second FE layer. (In the Web page, the
italicized words are originally in color.)
The italicized words are FEs composing the ATTACK frame. Among these,
Assailant and Victim are the core FEs, the most important ones for characterizing
the frame.
Selectional Restrictions 9
LUs are lexical or phrasal items that evoke a particular frame. BFN
identifies the following lexical items as LUs of the ATTACK frame:
LUs: attack, assail,,…
LUs are frame-evoking items. Verbs are regarded as the most important
among these and are sometimes called “governors” of frames because they provide
information for, or give names for, the frames evoked by them. For example, in the
sentence The man killed her with a gun, the verb kill tells us what occurs (i.e., who
did what to whom) and gives a name for the event that took place (KILLING or
MURDER).
The methodology of FrameNet appears very promising because the
structure of the semantic frame will be an effective means to describe the pieces of
world knowledge on which language comprehension is based and to which lexical
items are linked. For our purposes, however, it was necessary to obtain the detailed
semantics of the Japanese verb osou (which is polysemous, roughly meaning attack,
hit, and damage); this is because our research was conducted in Japan and one of
our goals was to provide a sample semantic analysis for Japanese based on FS in
order to illustrate its plausibility.
A project called Japanese FrameNet aims, according to its announcement,
at building a database of semantic frames for Japanese (Ohara, Fujii, Saito,
Ishizaki, Ohori, & Suzuki, 2003). But it is hard to believe now that the project
proceeded as planned: virtually nothing is available to us even three years after its
beginning: the semantic frame database has not yet been released in any form; any
serious result of text annotation for elements of semantic frames are published in
Selectional Restrictions 10
any form..
There is another, more critical problem: the granularity of the semantic
frames. The frames used in the BFN database proved to be too coarse-grained for
our purposes. Thus far, BFN has not provided a sufficiently detailed analysis of
semantic frames that could enable us to characterize the selectional restrictions (for
our target verb osou, for example) as co-variational semantics. Therefore, if the
Japanese FrameNet follows the BFN methodology, it is clear that the
characterization of the semantic frames relevant to osou will be inadequate for our
purposes.
The ATTACK frame cited above is responsible for the semantics of the verb
attack (also the noun attack), which corresponds to one of the senses of our target
verb, osou.
Semantic roles or FEs defined in BFN have two important features: first, as
shown in the definition above, the FEs identified in BFN are a more detailed,
verb-oriented concept than thematic roles such as Agent or Patient, which are
typically used in syntactic theories such as those of Jackendoff (1990) and Levin and
Rappaport (1991). Second, BFN definitions of semantic roles avoid reductionism;
they show as much or even more respect for the semantic aspects of language than
syntactic ones, thereby setting no priority on syntactic information over semantic
information. This is a desirable feature and is consistent with the results of studies
by McRae and his colleague (Ferretti et al, 2001; McRae et al., 1997, in press).
However, BFN-style characterization of semantic frames is not free of
problems; among the most crucial ones is that its definitions for frames are too
coarse-grained to achieve proper descriptions of selectional restrictions for a variety
of verbs. This problem can be illustrated by considering, for example, the detailed
Selectional Restrictions 11
semantics of attack. The above definition of the ATTACK frame is assumed to be
applicable to the class of events denoted by the verb attack. Thus, the events
denoted by the statements The robbers attacked the bank in the center of the city
and The lions attacked the impalas are appropriate instances of the ATTACK frame.
Therefore, on the one hand, the robbers realize the role of the Assailant and the
bank realizes the role of the Victim; on the other, the lions realize the role of the
Assailant and the impalas realize the (potential) role of the Victim. This is a correct
consequence. However, the background knowledge necessary for fully
understanding the two situations is clearly different. The robbers are a group of
gangsters who use violence and weapons for money, while the lions physically
damage the impalas for predation. Accordingly, (the) impalas cannot be Victims of
(the) robbers, (*The robbers attacked the impalas), while (the) lions cannot be
Assailants of (the) bank (*The lions attacked the bank in the center of the city). As
revealed by this contrast, it is necessary to have semantic frames identified at
finer-grained levels if we are to provide a precise description of the selectional
restriction phenomena shown in this manner. In other words, it is clearly desirable
for us to be able to specify semantic frames in much greater detail as long as we are
concerned with word sense disambiguation along with the selectional restrictions
imposed. This requires, as discussed above, the co-variational semantics of a verb
and its arguments. In addition, what is needed is to allow verbs to specify semantic
frames only at relatively more coarse-grained levels than nouns, as in the case of
the ATTACK frame in BFN. If this is right, semantic frames that account for the
meanings of sentences with a realized subject and objects possess much
finer-grained semantic specifications in terms of semantic frames.
Thus, to fulfill this requirement, the BFN methodology was extended and
Selectional Restrictions 12
slightly modified in our study. First, we decided to make no reference to the BFN
database. We then identified semantic frames that account for the entire range of
semantic variability of Japanese sentences in which osou is the main verb. This was
done independent of BFN since we expected to compare our definitions with the
BFN ones later. In this bootstrap process, we followed a fully bottom-up and blinded
procedure, which commenced with manual coding by linguists of sentences collected
from a Japanese newspaper corpus. The target included all the sentences in the
corpus whose main verb was osou.
In addition, the definition of semantic frames was slightly modified in our
study; it turned out to be restricted as compared with the one adopted by BFN. This
is because what we refer to as frames are, roughly speaking, restricted to
“situations,” while frames in BFN have a considerably wider denotational range. We
also posited a “template” for a frame. The template is a hierarchical organization of
semantic roles such as <<EFFECTIVE: what>, <GOVERNOR: do>, <what>,
<OBJECT: to what>, <MANNER: how>, <PURPOSE: for what>, <LOCATION:
where>, <TIME: when>, etc.
Third, we left out syntactic aspects such as Tense, Aspect, Voice, and
Modality from the description in order to concentrate on the semantic aspects of
phrases and sentences. (For details of theoretical aspects of our approach, see
Kuroda and Isahara, 2005.) The procedure adopted to specify the subsystem of
semantic frames for Japanese through corpus analysis is reported in the next
section.
Corpus Study
The corpus analysis methodology used in this study was based on the
Selectional Restrictions 13
semantic intuitions of linguists (specifically, the second and third authors of this
article) because there is almost no appropriate resource for describing meaning at
phrase and sentence levels. In this study, a Japanese verb osou was analyzed
because it has a variety of meanings.
The analysis proceeded as follows: (1) collecting all sentences containing
the verb osou from a newspaper corpus, (2) specifying the subject and object NPs of
the verb for each sentence, (3) identifying the semantic frame evoked by the verb
(and its arguments), (4) giving an appropriate name for the semantic frame and FEs
(in other words, semantic roles) composing the frame.
Linguistic data. Sentences that contained the verb osou were collected from
a corpus (Utiyama & Isahara, 2003). The corpus consisted of articles from a
Japanese newspaper that were published between 1989 and 2001. All sentences
were collected from the corpus, irrespective of the inflected forms of the verb; 413
sentences were collected in this manner.
Frame identification procedure. First, the subject and object NPs were
specified for each sentence that contained the verb. For example, for the first
sentence in Table 1, the NP the lions is the subject (i.e., the agent of attack) and a
herd of impala, the object (i.e., the patient).
Next, the semantic types of NPs were identified. “Semantic type” is a kind
of natural category labeling that can, in principle, be identified without referring to
the context of the NPs. For example, the semantic type of the lions is predator
animals. This kind of semantic analysis is typically found in ordinal thesauri like
WordNet (Fellbaum, 1998; Miller & Fellbaum, 1991).
-----------------------
Selectional Restrictions 14
Insert Table 1 about here
----------------------
The third and fourth phases were essential for this analysis. The third
phase was to identify the semantic roles of the subject and object NPs in each
sentence. Semantic roles correspond to BFN’s FEs, expressing lexical meanings that
are defined depending on the situation described by the sentence. For example, in
the sentence The lions attacked a herd of impalas, the semantic role of the subject
NP is predators and that of the object NP is prey. In order to comprehend the
concept of semantic roles, it might be helpful to compare the sentence with The lions
looked for a watering place. In this sentence, the semantic role of the lions is
searchers who are searching for a missing object. Semantic roles such as predator or
prey are dependent on the situation, represented as the preying attack frame. In
contrast, in the sentence The City Bank was attacked by three armed men, the
subject role is robbers and the object role is a storehouse of valuables in the robbery
frame.
In the fourth phase, the semantic frames that are instantiated by each
sentence were identified. The third and fourth phases were conducted in parallel
and in a circular manner. In other words, the analysts coded the situation that was
described by a specific sentence as a frame name, such as preying attack; at the
same time, they coded the semantic roles that the subject and the object NPs
realized in the understood situation. In some sentences, the coding of the semantic
role would precede that of the frame, especially in cases where the name used to
represent either the subject or object NP was the very label given to the semantic
role in the frame (e.g., robber for the robbery frame). For other sentences,
Selectional Restrictions 15
identification of the frame would precede that of the roles, especially in cases with
no lexical item denoting a semantic role directly. In this case, the analysts had to
decide which situation was described in the sentence based on their interpretation
of its contents As mentioned above, the analysis was based solely on the semantic
intuition of two linguists, without making any reference to the BFN database.
Results of the corpus analysis. On the basis of the corpus analysis described
above, 15 semantic frames were identified for the situations described by the
sentences containing osou. The frames are listed in Table 2.
-----------------------
Insert Table 2 about here
----------------------
The meanings of osou correspond approximately to attack, hit, and damage in
English.The frames from F01 to F05 are defined as situations in which human
assailants bodily damage other human victims, or carry out violent acts for a specific
purpose. F06 and F07 are frames in which the Agent (Assailant) is animal(s) and the
Patient (Victim) is animate being(s). These frames (F01 to F07) are often expressed by
attack in English. The frames from F08 to F12 are defined as situations in which
incidental damage is caused to humans. In these frames, the subject NPs
(Harm-causers) are typically inanimate things, and there is no intention of causing
harm. F08 typically has a machine or manmade accident name as the Harm-causer and
a noun referring to human beings (either literally or metonymically) as the Victim. F09
and F10 are frames that express the damage caused by natural disasters to human
beings and their activities. Typically, F09 is realized by a subject NP that denotes a
Selectional Restrictions 16
large-scale natural disaster and an object NP that denotes a place or an area name. In
contrast, F10 is usually realized by a subject NP denoting a small-scale natural disaster
and an object NP denoting a small number of human beings. The F11 and F12 are
frames in which the name of a place or organization is a typical NP for the Victim. F11 is
the frame that typically has an NP that refers to an epidemic disease as a subject. In
contrast, F12 has the name of an (economic) activity or event as the subject NP. The
frames from F09 to F12 are typically expressed by damage or hit in English. F13–F14
are frames in which a single human being is harmed by a mental or physical illness.
The typical NPs for Harm-causer are names of diseases or negative emotions, while
those for Victims are nouns denoting a single human being. These frames also display
no clear intention of causing harm. For a comparison of these frames with BFN, see
Kanamaru, Kuroda, Murata, and Isahara (to appear).
It should be noted that the identification of the frames and the selectional
restrictions of osou are closely related. For example, if the subject of osou is an NP
denoting robbers (e.g., the robbery team), plausible NPs for the object are restricted to
those that refer to institutions or persons who possess valuables such as money or
jewelry. In general, subject NPs denoting animate beings tend to co-occur with object
NPs referring to animate beings; however, there are a few exceptions, such as the
robbery (F03) or the invasion (F02) frames, in which the object NP tends to be a phrase
that refers to an institute or a small place such as a bank or a military base. In most
cases, however, animate beings “attack” animate beings such as a group of humans or
animals. They hardly take an object NP that refers to a large place, like Asian countries,
as victims. In contrast, inanimate subjects take either animate or inanimate entities as
an object NP, depending on their scales. If the subject NP denotes something that is
relatively large (e.g., typhoon), the object NP for the verb tends to refer to a large place
Selectional Restrictions 17
or area (e.g., Kyusyu area). In contrast, when the subject NP denotes a relatively small
event, like sleepiness, that takes place in a single person’s body, it is likely to take an
animate being, particularly a human being, as an object.
Since these results were obtained by depending solely on the intuition of
the linguists, psychological experiments were conducted to confirm the validity of
the semantic frames (Nakamoto et al., in press). In these experiments, participants
were required to sort sentences containing osou based on their semantic similarity.
The results demonstrated that the clustering of the sentences by laypersons was
fairly consistent with the analysis of the linguists.
The results of the corpus analysis showed that there exists a contingency
between the specified semantic frames and the semantic types of the subject or
object NPs in a sentence denoting a specific frame. For example, NPs that can be
the subject in a sentence referring to the frame spreading of an epidemic are limited
to those that denote the name of an epidemic (e.g., plague) or those that contain the
name of the epidemic (e.g., spread of the plague). However, it is impossible to
completely specify the semantic frame with the subject or object NP alone. A simple
example is the following pair: The plague attacked his daughter and The plague
attacked the Asian countries. Although the two sentences have the same phrase as
their subject, the former refers to the frame getting sick and the latter to the frame
spreading of an epidemic. This example demonstrates that the senses of noun
phrases and verbs are dependent on each other.
These results suggest that the selectional restrictions that operate in a
sentence headed by osou must be described in terms of co-variational semantics,
given a set of arguments of the verb. More generally, it can be stated that the
semantic frame or situation determined interactively by all words in a sentence
Selectional Restrictions 18
restricts and narrows the combinatorial range of the arguments for a given verb.
This implies that assuming strict compositionality in semantic operations fails to
capture an important aspect of sentence meaning construction because it fails to
properly characterize the effect of “mutual semantic accommodation” among the
words in a sentence (Langacker 1987, 1991) and the effect of co-compositionality
that arises from them (Pustejovsky 1995).
However, there were some limitations in the corpus analysis. One of them
was the nature of the corpus per se—no corpus can contain all the possible linguistic
expressions. In order to overcome this, psycholinguistic experiments were
conducted in this study. In the next section, we will illustrate the experimental
materials that were created, based on the results of the corpus analysis.
Experimental Materials
In the following experiments, we asked participants to choose words or
phrases that could fill a blank in a sentence like O was/were attacked by ____ (O ga
_____ ni osowareta), where O was the object NP of the verb. Adopting this procedure,
the intuition of laypersons with regard to selectional restrictions can be estimated
more directly and systematically. Evidently, in order to obtain a precise estimation
of their linguistic intuition, appropriate preparation of the experimental materials
was required. The results already obtained from the corpus analysis were useful for
this purpose.
As described in the previous section, there exist typical semantic types of
the subject and object NPs for each semantic frame. For example, in a sentence
expressing the frame violence (F05), the object NP is typically a single individual or
a small group of people who are vulnerable to violence. In the case of osou, more
Selectional Restrictions 19
varieties of semantic types can serve as subject NPs than as object NPs. NPs
denoting humans, organizations, animals, natural disasters, or diseases can serve
the purpose of a subject. In contrast, semantic types that can serve as Victims are
typically limited to NPs denoting humans, animals, activities, or places.
Based on these observations, typical subject and object NPs were selected
for each semantic frame. Three frames were divided into sub frames because they
contained possibilities for further sub-clustering. The NPs chosen for the
experiments are shown in Table 2. In the table, materials are paired such that each
NP-verb pair naturally evokes each frame. While preparing the materials, we
avoided strongly lexically associated pairs, such as gangsters and gang boss, as
carefully as possible in order to make it possible for an NP to combine with two or
more NPs. It should be noted, however, that the possible combinations of the NPs
are not restricted to those in Table 2. For example, the subject NP a new type of
pneumonia can damage statesman as well as Asian countries. Based on this
flexibility of possible pairing, it was expected that the results of the experiments
will reveal a general pattern of the selectional restrictions of the verb osou. More
precisely, it was predicted that an argument that originated from the same frame as
that denoted by the sentence containing the other argument would be chosen most
frequently; further, that the other argument that, when inserted in the blank,
would make the sentence meaningful (i.e., could realize one of the semantic frames)
would also be chosen with some frequency.
For Experiment 1, the object NPs in Table 2 were embedded in the active
( ____ attacked O) and passive (O was/were attacked by ____) sentences. Eighteen
subject NPs were used in the multiple-choice items for the blanks. For Experiment
2, the subject NPs were embedded in the active (S attacked _____) and the passive
Selectional Restrictions 20
( ____ was/were attacked by S), and 18 object NPs were used in the multiple-choice
items.
Experiment 1: Subject NP Choice
In Experiment 1, the participants were required to fill the blank at the
subject NP position by choosing more than one of the words or phrases listed in
Table 2. The purpose of Experiment 1 was twofold: (a) to find the selection patterns
of subject NPs for each object NP and (b) to compare the response patterns in the
active and passive forms.
The first purpose is addressed to validate our claim that the selectional
restrictions are determined by semantic frames. If our claim is valid, we should find
consistent patterns in the subject NP choices that can be predicted by the semantic
frame analysis. The second purpose was supplementary: by comparing the choice
patterns in the active and passive forms, it was examined whether or not the
situation knowledge that is evoked by the object NP and the verb osou was different
for the superficial grammatical forms.
Method
Apparatus and procedure. Eighteen sentences in the forms of ____ attacked
O ( ____ ga O o osotta) (for the active condition) and O was/were attacked by ____ (O
ga ____ ni osowareta) (for the passive condition) were used as experimental
materials. The Os in the sentences were filled with the object NPs in Table 2.
Eighteen subject NPs served as the choice items for the blanks.
Separate booklets comprising four pages each were prepared for the active
and passive conditions. The first page included instructions for participants to fill
the blanks in the sentences by choosing words and phrases from among 18 items.
Selectional Restrictions 21
When a word or phrase appeared to be perfectly suited to the sentence, the
participants were required to mark it with a circle. If they felt that the word or
phrase would possibly suit the sentence but were not be completely confident, they
were required to mark it with a triangle. They were allowed to mark as many choice
items as they judged fit with both a circle and a triangle. Six sets of the sentence
and the corresponding 18 choice items (subject NPs) were printed per page on the
other pages of the booklets. The sentences were printed in a random order that
differed for each participant. The order of the 18 choice items was also randomized
for each sentence.
The experiment was conducted in three separate classrooms. The
participants received a booklet that contained 18 active or passive sentences, and
were instructed to complete the booklet at their own pace. It took about 20 minutes
for the task to be completed.
Participants. Thirty-nine university and college students participated in
the experiment; 18 of them were assigned to the active form and 21 to the passive
form. All were native Japanese speakers.
Results and Discussion
On an average, the participants in the active form condition chose 3.48
items (SD = 2.41) as “perfectly suitable” and 1.40 items (SD = 0.84) as “possible” per
sentence. In the passive form condition, the mean number of the items chosen as
“perfectly suitable” was 3.03 (SD = 2.11) and that of the items chosen as “possible”
was 0.65 (SD = 0.71).
Only perfectly-suitable responses were used in the following analysis
because it was better to measure the participants’ primary intuition than to use all
the responses. In order to identify a general tendency for the selectional restrictions
Selectional Restrictions 22
for osou, the responses were collapsed across all participants for each condition.
Table 4 shows the number of times that the subject NP was chosen for each sentence
containing an object NP.
--------------
Insert Table 3 about here
------------
In general, as shown in Table 4, the participants chose subject NPs for
object NPs that were chosen from the same semantic frames more frequently than
most of the other items. The observed patterns were very similar for the two
grammatical forms.
To confirm these tendencies statistically, a log-linear analysis was
conducted on the frequency table by using HILOGLINEAR (for model selection) and
LOGLINEAR (for parameter estimation) procedures in SPSS2.
The analysis revealed that there was no significant effect of the
grammatical forms. The effect of the grammatical form had no significance, both on
the main effect and on the interactions with the other variables. The model selected
as the best presumed that the choice patterns of the subjects were different among
the object NPs. A summary of the hierarchical deletion steps of the factors is
presented in Table 4. The standardized effects estimated with the selected model
are shown in Table 3.
---------------
Insert Table 4 about here
Selectional Restrictions 23
-----------------
The log-linear analysis confirmed the tendency described above: the subject
NP that matched the object NP in each sentence was likely to be chosen most
frequently. It was also revealed that the object NPs denoting non-human objects
(such as Asian countries or transportation firm) induced the participants to choose
non-human subject NPs. In contrast, when the object NP denoted humans, various
types of subject NPs tended to be chosen. However, the patterns of item choice were
different for the different types of human object NPs. The object NPs referring to
relatively weak persons (e.g., a mother and her children) prompted the participants
to choose the subject NPs that denoted animate things, while the object NPs
referring to relatively strong persons (e.g., effective manager) elicited inanimate
subject choices (tumor).
A correspondence analysis was conducted in order to obtain the overall
contingency pattern of the object and subject NPs. Figure 1 shows a
two-dimensional solution of the correspondence analysis. These dimensions
accounted for 29.3 % and 23.4 %, respectively, of the total inertia.
-----------------------------
Insert Figure 1 about here.
---------------------------
Figure 1 shows that the first dimension (horizontal axis) reflects the scale
of the damages. On the right side of the map are the object NPs referring to areas or
large-scale institutions (e.g., Asian countries) and the subject NPs referring to
Selectional Restrictions 24
inanimate or abstract entities (e.g., new type of pneumonia). In contrast, the object
NPs denoting animate beings (especially humans) and the subject NPs referring to
animate beings or an abnormality of the body and mind are plotted on the left. The
second dimension (vertical axis) can be roughly interpreted to reflect the distinction
between natural and manmade damages. On the lower half of the display, the
subject NPs denoting animals, diseases and natural disasters (e.g., lions, large
typhoon, and sleepiness) are plotted. On the upper side are the subject NPs relevant
to human activities (e.g., stock crash, mob).
It is notable that the correspondence analysis clearly demonstrates the
contingency of the object and the subject NPs. The type of object NP that was
embedded in the sentence restricted possible subject NPs, although the verb
contained in the sentence was the same across all materials. Moreover, all object
NPs presented in the sentences were potential victims of attacking or hitting events.
These results might be problematic for purely verb-based approaches to sentence
semantics because the pattern of the participants’ choice was hardly interpreted as
a set of constraints purely imposed by the verb. If we assume that the verb has
sufficient information for characterizing the contingency pattern of the subject and
object NPs, there is almost no difference between the purely verb-based approaches
and ours because such a characterization clearly demands a detailed knowledge of
world events. More importantly, such a modification of the verb-based approach
may result in assumptions of word meaning representations that are far from
realistic.
Therefore, we claim that it is more straightforward to consider that the
contingency between the subject and the object NPs reflects mental representation
based on the semantic frame. The participants chose the subject-object pairs that
Selectional Restrictions 25
instantiate the semantic frames identified through the corpus analysis. In other
words, the results imply that the participants chose the appropriate NPs by using
their knowledge regarding the types of Harm-causers that can inflict damage to
specific types of potential victims.
Experiment 2: Object NP Choice
Experiment 2, in contrast to Experiment 1, investigated the patterns of
object NP choices for sentences containing the subject NPs and osou.
Method
Apparatus and Procedure. The apparatus and the procedure of this
experiment were the same as those in Experiment 1, except that the subject NPs
were given in the sentences and the object NPs served as multiple-choice items.
Participants. Forty university and college students participated in the
experiment. Twenty of them were assigned to the active form and the rest to the
passive form. All were native Japanese speakers.
Results and Discussion
The collected responses were analyzed in the same way as in Experiment 1.
On an average, the participants in the active form condition chose 4.33 items (SD =
2.21) as “perfectly suitable” and 1.16 items (SD = 0.75) as “possible” per sentence. In
the passive form condition, the mean number of the items chosen as “perfectly
suitable” was 4.26 (SD = 2.07) and the mean number of the items chosen as
“possible” was 0.87 (SD = 0.77).
Table 5 summarizes the number of times that each object NP was chosen
for each subject NP. The object NPs that match the subject NPs in terms of the
semantic frames were frequently chosen, like in Experiment 1. However, there
Selectional Restrictions 26
appeared to be some differences between the results obtained from the two
experiments: compared with those in Experiment 1, the choices for some object NPs
(e.g., woman living alone) were selected more often in the passive form condition
than in the active form condition.
-------------
Insert Table 5 about here
---------------
To test these tendencies statistically, a log-linear analysis was conducted
with SPSS. A hierarchical log-linear analysis selected the model containing three
main effects (grammatical form (Voice, V), subject NPs (Sub), object NPs (Obj)) and
first-order interactions (V X Sub, V X Obj, Sub X Obj), but without the second-order
interaction (V X Sub X Obj)3. The goodness of fit index (G2) of the selected model and
that of the others are shown in Table 6. The standardized effects estimated in the
model are also shown in Table 5.
---------------------
Insert Table 6 about here
---------------------
Although the hierarchical modeling selected the model with interaction
between the grammatical forms and the other variables, there was no subject-object
pair that had significantly different choice frequencies between the active and
passive forms, as shown in Table 5. Therefore, we decided to conduct the following
Selectional Restrictions 27
analysis using data collapsed across the grammatical forms.
A correspondence analysis of the collapsed data was conducted in order to
understand the choice patterns of the object NPs for each subject NP. The first and
the second dimensions accounted for 38.9 % and 20.9 % of the total variance,
respectively. Figure 2 shows the map of the two-dimensional solution.
-----------------------------
Insert Figure 2 about here.
---------------------------
Figure 2 shows configurations that are very similar to those in Experiment
1; again, the first dimension differentiated the scale of the damage caused by the
attacking (hitting) events, and the second distinguished whether the damage was
caused by natural events or human activities. The similarity of the results in the
two experiments suggests that evocation of the frames depends mainly on the
combinations of the verb and its arguments, regardless of the surface grammatical
forms. This is consistent with the definition of semantic frames because they are
assumed to be units of semantic understanding, not grammatical understanding.
The left side of Figure 2, however, shows a difference from Figure 1.
Comparing this to the results of Experiment 1, Figure 2 does not differentiate
between the natural and artificial nature of the attacking or hitting events when
the damages are relatively small. The difference between the two experiments
might reflect the distinctiveness of the choice responses. In Experiment 1, the choice
patterns of the subject NPs were similar among the object NPs that had similar
attributes. For example, the subject-choice frequency for the NPs small country in
Selectional Restrictions 28
the Middle East, Kyusyu area, and Asian countries, which had attributes such as
[inanimate, place, etc], showed high correlations (.82, .85, .77, respectively). As a
result, the differentiation among the semantic frames was observed, as had been
intended when we prepared the materials (see Table 2). In contrast, the choice
patterns among similar object NPs did not show such extremely high correlations
(for example, the correlation between stalker and drug addict was .60). It may be
possible to account for this by positing that the discrepancy between the two results
was caused by the difference in the strengths of the connections linking the NPs to
the semantic frames. In other words, the constraints on the object NPs, imposed by
the combination of the verb and its subject NP, might be stricter than those on the
subject imposed by the verb and its object NP. However, this is merely a hypothesis
based on rudimentary informal observation. Further work is required to draw such
a conclusion.
General Discussion
The results from the two experiments revealed that the verb osou imposes a
set of constraints on the combination of subject and object. Moreover, the
contingency patterns obtained from the participants’ NP choices were fairly
consistent with the predictions of the results of the frame-based corpus analysis.
That is, subject NPs denoting animate beings tend to associate with object NPs
denoting animate beings or small-scale institutions, while inanimate subject NPs
could associate with both animate and inanimate object NPs. In addition, the
participants displayed choice patterns that were fairly consistent with the semantic
frame analysis by the linguists. In many cases, the most frequently chosen
argument was one that came from the same sentence that contained another
Selectional Restrictions 29
argument.
These results support our claims that selectional restrictions are based on
semantic frames rather than lexical restrictions imposed by the verb, the head of a
sentence. As described in the introduction, some studies have reported that a verb is
not the only source of information for selectional restrictions or thematic role
assignments (Kamide, Altman, & Haywood, 2003; McRae, Hare, Elman, & Ferretti,
in press; McRae, Hare, Ferretti, & Elman, 2001; Vu, Kellas, Petersen, & Metcalf,
2003). However, there appears to be no adequate approach to selectional restrictions
thus far; a general theory is yet to emerge.
The scope of the present study is clearly limited because it is based on
examples that rely on just one Japanese verb, osou. However, the study
demonstrates that a recognizable subset of selectional restrictions can be explained
quite naturally as “adaptations” of word senses to their “environments,” which are
represented as semantic frames, given that semantic frames specify units of human
situational understanding or schemas for (idealized) situations. As far as this
account is sufficiently natural and generalizable to a reasonable degree, it suggests
that an approach based on semantic frames can, and will, provide a general account
of selectional restrictions.
However, there is one caveat. Despite the promise it holds, such an account
requires an appropriate degree of granularity in semantic description, and it is
evident that existing definitions of relevant semantic frames in BFN are not
sufficiently fine-grained. This implies that adopting FS is insufficient to account for
selectional restrictions in general: it must be done at an appropriate level of
detailed world knowledge. This would make certain modifications to the BFN
framework unavoidable.
Selectional Restrictions 30
The results of this study, which indicate that selectional restrictions to the
arguments correlate with the sense disambiguation of a verb, are consistent with
Hare, McRae, and Elman (2004). Their study demonstrated that the correlation
between meaning and syntactic structure is based on the specific senses of verbs
and not on the verbs themselves. Although their research focused on a syntactic
subcategorization of English verbs, a correspondence between their results and ours
is obvious. That is, to reveal the relationship between the meanings and structure of
languages, it is crucial to consider semantics at a fine-grained, context-sensitive
sense level and not at a coarse-grained, verb-general meaning level. The corpus
analysis procedure we proposed in this article will provide a coherent means of
identifying senses that a verb realizes with its arguments in different contexts.
In addition to implications with regard to the relationship between
linguistic expressions and knowledge of events, our results suggest that the naive
compositional view of sentence meaning must be reconsidered. In general,
traditional approaches to linguistic meaning implicitly assume that sentence
meaning can be described as a composition of lexical meanings of words in a
sentence according to their positions in a syntactic structure, as Traxler, Pickering,
and McElree (2002) suggested. It is true that many theoretical and empirical
studies have claimed that there are some aspects of sentence meaning that cannot
be reduced to lexical ones (e.g., Goldberg, 1995; Pustejovsky, 1995). Nonetheless,
few empirically valid theories have been proposed that are able to deal with the
relationship between sentence and word meaning sufficiently. As a result, questions
such as how meanings at the sentence level should be linked to meanings at the
lexical level remain unresolved, and empirical studies have been conducted with no
theoretical background in this regard.
Selectional Restrictions 31
For example, studies on the comprehension of polysemous words (e.g.,
Frazier & Rayner, 1990; Klein & Murphy, 2001, 2002; Vu et al., 2003) focus on the
process involved in sense disambiguation pertinent to their contexts (i.e., the
co-occurring words). In these studies, however, detailed content of the contextual
effects on word meaning has not been treated directly, that is, there is no detailed
description of what exactly is implied by the term “context.” We suspect that,
beneath this shortcoming, contextual effects are implicitly assumed to be
one-directional, especially when considering the (preceding) contextual effect on the
recognition of target words in experimental settings. However, our results suggest
that the contextual effects on the comprehension of word meanings are more subtle
and complicated than previous studies have probably assumed implicitly. Words in
a sentence would play a contextual role for each other in order to disambiguate their
senses. Recently, Pickering and Frisson (2001) proposed a model that explains that
the recognition of polysemous words begins with the underspecification of multiple
senses, and disambiguation is achieved when related information is provided by the
following context. Although their claim is very insightful for the purpose of
revealing how language is processed, it is difficult to acquire a complete
understanding of the underlying mechanism without an appropriate description of
the connections between sentence-level linguistic expressions and knowledge of
situations and events.
In addition, the evidence presented in this study questions the basic
assumptions of the traditional (particularly verb-based) approaches to sentence
meanings. Our basic notion, that sentence (or phrase) meanings should be defined
as connections between combinations of multiple words and situation concepts,
implies that it would be invalid to reduce a whole sentence meaning to a
Selectional Restrictions 32
composition of individual word meanings. In other words, meanings at the sentence
level show Gestalt-like properties, which cannot be reduced to meanings at the
lexical level. This implication is notable because there is no semantic theory that
characterizes sentence meanings in this way. Although several studies have argued
that situation knowledge plays an essential role in sentence comprehension
(Ferretti et al., 2001; McRae et al., 1997, 2001, in press; Vu et al., 2003), they have
tended to assume that the activation of a situation concept will be attributed to a
single word such as a subject, object, or verb. The co-variational semantic view, at
least, has not been instantiated in the experimental manipulation. This study
cautions against this kind of reductionism and impresses upon us the need to
develop a framework that describes the nature of contextual effects in greater detail.
It is especially important to specify which parts of a linguistic expression work in
cooperation to achieve an appropriate disambiguation and to acquire a coherent
understanding of a sentence.
In summary, this study demonstrated that the contribution of frame-based
corpus analysis and the evaluation of its results by psychological experiments is a
powerful method of investigating phenomena related to sentence-level
comprehension, such as selectional restrictions. It will provide a new method to
clarify the linguistic and psychological aspects of semantic understanding.
Selectional Restrictions 33
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Selectional Restrictions 38
Footnotes
1 An interesting version of such co-variational and co-compositional semantics is
provided in Pustejovsky (1991, 1995); however, we require more refinement from a
psycholinguistic perspective.
2 Strictly speaking, the log linear analysis might not be appropriate because the
responses in the table were not independent of each other (Please recall that each
participant made multiple choices for each object NP). In this study, however, the
response patterns among the participants were highly similar. Therefore, we
decided to collapse the data across the participants in order to make the statistical
results simple and intelligible. In the analysis, Delta was set at .5.
3 The model containing the second-order interaction was saturated.
Selectional Restrictions 39
Selectional Restrictions 40
Table 1
Examples of the semantic frame analysis
Prior context Key verb Following
context
Arg NP Semantic
type
Semantic
role
Semantic
frame
The lions attacked a herd of impalas. Subject the lions animal
[+predatory]
Predator Preying
attack
Object a herd of
impalas
animal
[–predatory]
Prey
The City
Bank
was
attacked
by three armed
robbers.
Subject three armed
men
human
[+grouped]
Robber Robbery
Object the City
Bank
institution Storage of
valuables
Note. For ease of understanding, this table was created with examples in
English, using attack as a translation of the Japanese verb osou. However,
not all meanings of osou translate into the word attack.
Selectional Restrictions 41
Table 2.
List of the semantic frames of “x ga y o osou” (x attacked y)
Frame Example Translation
F01A: bouto ga keikan tai o osotta.
Denoting harm to y caused
by a conflict between x and y
(x’s intentionality is unclear) A mob (SUBJ-pp) police squad (OBJ-pp) attacked
A mob attacked the squad of police.
futari no boukan ga hoshuha no seijika o osotta F01B: Denoting harm to y caused
by a conflict between x and y
(x’s intentionality is clear)
two ruffians (SUBJ-pp) conservative statesman (OBJ-pp)
attacked
Two ruffians attacked the
conservative statesman.
F02: shigen ni toboshii kuni ga chuutou no shoukoku o osotta
Denoting harm to y caused
by x’s invasion country with few resources (SUBJ-pp) small country in the Middle
East (OBJ-pp) attacked
A country with few resourcse
attacked the small country in the
Middle East.
Selectional Restrictions 42
F03: Sannin no otoko ga ginkou o osotta Three men attacked the bank.
Denoting harm to y caused
by x’s robbery three men (SUBJ-pp) bank (OBJ-pp) attacked
F04: mushoku no otoko ga hitori gurashi no josei o osotta
Denoting harm to y caused
by x’s committing rape unemployed man (SUBJ-pp) woman living alone (OBJ-pp)
assaulted
An unemployed man assaulted a
woman living alone.
F05A: toorima ga suumei no shougakusei o osotta
Denoting harm to y caused
by x’s violence (y is chosen
as weak persons by x.)
murderer (SUBJ-pp) several elementary school students (OBJ-pp)
assaulted
A murderer assaulted several
elementary school students.
F05B: yakubutsu chuudoku no otoko ga tsuukounin o osotta
Denoting harm to y caused
by x’s violence (wihtout clear
intention for choice of
victims)
drug addict (SUBJ-pp) pedestrians (OBJ-pp) assaulted
A drug addict assaulted pedestrians.
F06: Denoting harm to y caused raion ga inpara no mure o osotta The lions attacked a herd of impalas.
Selectional Restrictions 43
by x’s preying attack lions (SUBJ-pp) herd of impalas (OBJ-pp) attacked
F07: dokuhebi ga tozankyaku o osotta
Denoting harm to y caused
by x’s non-preying attack poisonous snake (SUBJ-pp) hiker (OBJ-pp) attacked
A poisonous snake attacked the
hiker.
F08: bousou trakku ga soyakozure o osotta
Denoting harm to y due to
an unexpected accident x Out-of-control truck (SUBJ-pp) mother and her son (OBJ-pp) hit
A truck out of control hit the mother
and her son.
F09: oogata no taifu ga nihon o osotta A large typhoon hit Japan.
Denoting harm to y caused
by a natural disaster x (on a
large scale) large typhoon (SUBJ-pp) Japan (OBJ-pp) hit
F10: toppu ga TV no repootaa o osotta
Denoting harm to y caused
by a natural disaster x (on a
small scale) a gust (SUBJ-pp) TV reporter (OBJ-pp) hit
A gust of wind hit the TV reporter.
F11: Denoting harm to y caused Supein kaze ga ajia shokoku o osotta The Spanish influenza hit Asian
Selectional Restrictions 44
by the spread of an epidemic
x Spanish Influenza (SUBJ-pp) Asian countries (OBJ-pp) hit
countries.
F12: oogata no fukyou ga nanbei no kuniguni o osotta
Denoting harm to y caused
by a social phenomenon x
(large scale) large recession (SUBJ-pp) South American countries (OBJ-pp) hit
A large recession hit the South
American countries.
F12: daikibo na ristora ga unsou kanren no kaisya o osotta
Denoting harm to y caused
by a social phenomenon x
(small scale).
Corporate downsizing (SUBJ-pp) transportation company
(OBJ-pp) hit
Corporate downsizing hit the
transportation company.
F13: akusei no gan ga hatarakizakari no dansei o osotta
Denoting harm to y caused
by a disease x
(non-temporary) malignant tumor (SUBJ-pp) man in his prime(OBJ-pp) attack
A malignant tumor attacked the
man in his prime.
F14: Denoting harm to y caused suima ga yukiyama sounansha o osotta Sleepiness attacked the man lost in
Selectional Restrictions 45
by a disease symptom x
(temporary)
Sleepiness (SUBJ-pp) climber lost in the mountain in winter
(OBJ-pp) attacked
the moutain in winter.
F15: fukitsu na yokan ga binwan no shachou o osotta
Denoting harm to y caused
by a feeling x (temporary) Sense of foreboding (SUBJ-pp) effective manager (OBJ-pp)
attacked
A sense of foreboding attacked the
effective manager.
Note. The italicized phrases were used as materials in the experiments. (SUBJ-pp) and (OBJ-pp) denote the past
positions marking the subject and object phrases, respectively. Although some of these frames contain verbs other
than attack in the English translation (e.g., hit), it is natural for the Japanese to express the words in these frames
using the verb osou. The (pp)s denote post positions.
Selectional Restrictions 46
Table 3
Choice frequency of each subject NP as a function of object NPs given in sentences (Experiment 1)
Object NPs embedded in the sentences
Subject NPs
(choice items) F01A
: squ
ad o
f pol
ice
F01B
: sta
tesm
an
F02:
smal
l cou
ntry
in th
e M
iddl
e Ea
st
F03:
ban
k in
Tok
yo
F04:
wom
an li
ving
alo
ne
F05A
: ped
estri
ans
F05B
: prim
ary
scho
ol st
uden
ts
F06:
her
d of
impa
las
F07:
mou
ntai
n hi
ker
F08:
mot
her a
nd h
er so
n
F09:
Kyu
syu
area
F10:
hou
se
F11:
Asi
an c
ount
ries
F12A
: mar
ket
F12B
: tra
nspo
rt co
mpa
ny
F13:
man
in h
is p
rime
F14:
clim
ber l
ost i
n th
e m
outa
in in
win
ter
F15:
eff
ectiv
e m
anag
er
Total
16 8 2 8 1 9 5 1 1 6 1 2 1 4 9 2 1 5 82
15 9 3 10 5 11 6 0 1 6 1 4 1 2 4 2 1 5 86
F01a mob
5.54* 1.06 -0.17 3.78* -1.91 3.87* 0.28 -1.33 -1.43 0.38 -0.52 -0.14 -0.72 2.56* 1.76 -2.41* -1.32 -1.23 5.37*
Selectional Restrictions 47
7 6 2 3 11 7 7 1 1 9 0 2 0 0 4 4 1 6 71
3 7 0 5 13 6 8 0 1 7 0 2 0 0 1 3 1 7 64
F01b Two ruffians
1.90 1.44 -0.71 1.97* 3.81* 3.32* 2.61* -0.76 -0.70 2.69* -1.16 0.01 -1.26 -0.77 0.11 -0.35 -0.59 0.94 0.96
0 2 8 0 0 0 0 0 0 0 2 0 4 0 0 0 0 0 16
0 2 4 0 0 0 0 1 0 0 1 0 2 0 1 1 0 1 13
F02 country with
few resoures
-0.75 1.52 6.40* -0.50 -1.13 -0.55 -0.93 1.05 -0.48 -0.97 3.21* -0.60 4.80* 0.33 0.21 -0.42 -0.43 -0.63 -4.90*
7 11 0 14 9 10 12 1 2 11 0 9 0 0 7 6 1 10 110
7 13 0 11 15 11 13 2 5 14 0 5 0 0 7 6 2 12 123
F03 three men
1.82 2.40* -1.91 4.86* 2.30* 3.84* 3.25* -0.26 0.64 3.08* -1.48 2.34* -1.57 -1.08 1.96* -0.07 -0.80 1.47 3.38*
3 2 0 1 17 4 4 0 0 5 1 1 0 0 1 2 1 5 47
0 3 0 0 21 0 3 0 0 2 0 0 0 0 0 2 0 7 38
F04 stalker
0.49 0.57 -1.04 -0.34 7.90* 1.52 1.93 -0.76 -1.04 1.80 0.39 -0.51 -0.72 -0.22 -0.72 0.12 -0.22 2.68* -2.66*
7 6 0 7 10 14 11 0 0 11 0 4 0 0 7 8 1 8 94
8 7 0 4 8 12 12 0 0 13 0 2 0 0 2 5 0 7 80
F05a drug addict
3.38* 1.58 -1.53 3.05* 2.64* 5.85* 4.28* -1.25 -1.53 4.30* -1.10 1.03 -1.20 -0.71 1.79 1.61 -1.04 1.58 0.43
Selectional Restrictions 48
4 6 1 2 10 18 12 0 1 13 1 3 0 0 2 5 1 6 85
3 10 0 1 18 15 18 0 1 15 0 1 0 0 0 8 0 8 98
F05b murderer
0.82 2.16* -1.24 -0.23 4.42* 6.87* 5.44* -1.31 -0.71 4.96* -0.52 0.00 -1.27 -0.77 -1.24 1.44 -1.15 1.16 0.96
3 2 1 1 2 3 4 18 4 6 0 1 0 1 1 3 2 3 55
2 1 1 0 0 2 4 20 5 7 0 2 0 0 0 2 2 4 52
F06 lions
0.54 -1.33 -0.35 -0.98 -1.75 1.06 1.16 9.83* 2.96* 2.61* -1.00 -0.06 -1.09 0.41 -1.37 -0.53 0.92 -0.21 -0.38
2 3 2 1 3 3 6 9 14 9 1 3 0 0 2 4 6 2 70
2 1 2 0 2 7 7 9 13 9 0 3 0 0 0 2 4 6 67
F07 wild boar
-0.58 -1.61 0.14 -1.38 -1.32 2.25* 1.86 5.70* 6.42* 2.94* -0.63 0.69 -1.33 -0.83 -1.39 -0.92 2.77* -0.72 1.63
6 3 0 4 2 10 9 1 1 12 0 9 0 0 5 4 1 3 70
9 5 0 4 4 9 9 0 3 12 0 8 0 1 4 7 0 2 77
F08 truck out of
control
3.25* -0.12 -1.62 1.89 -0.83 4.62* 3.21* -0.79 0.26 4.24* -1.19 4.23* -1.29 0.10 1.59 0.82 -1.18 -1.49 1.13
1 0 14 3 0 0 0 3 6 1 18 11 15 1 4 0 5 0 82
0 0 9 1 2 2 1 4 6 1 20 14 12 1 2 1 4 0 80
F09 large typhoon
-1.67 -2.22* 5.97* 0.31 -2.09* -0.82 -1.99* 2.53* 3.41* -1.74 9.50* 6.11* 7.35* 1.00 0.58 -2.30* 2.67* -2.35* 0.88
Selectional Restrictions 49
1 1 3 1 1 2 4 4 16 4 4 13 1 0 2 1 10 1 69
4 2 7 1 3 4 4 4 19 7 6 16 3 0 4 2 9 3 98
F10 landslide
-0.84 -2.53* 1.78 -1.37 -2.31* 0.15 -0.44 2.03* 6.90* 0.28 3.19* 5.79* 0.40 -1.06 -0.40 -2.53* 4.52* -2.62* 4.33*
1 3 11 0 3 0 2 3 1 1 9 1 14 0 1 7 1 3 61
1 6 12 0 7 0 3 1 3 0 4 2 9 0 0 15 3 8 74
F11 new type of
pneumonia
-1.17 0.46 6.04* -1.56 0.70 -1.61 -0.36 1.18 0.45 -1.99* 5.14* -0.35 6.78* -0.72 -1.57 3.83* 0.60 0.60 0.56
0 3 9 11 0 0 0 0 0 0 1 0 13 18 8 1 0 10 74
0 6 7 14 1 0 0 0 0 0 0 0 10 19 11 1 0 10 79
F12a stock crash
-1.42 1.72 5.50* 7.16* -1.57 -1.21 -1.60 -0.87 -1.15 -1.64 0.21 -1.27 7.50* 10.41* 5.69* -1.09 -1.09 3.99* -1.78
1 2 3 8 3 0 0 0 0 2 2 1 2 4 13 12 0 1 54
3 2 1 7 6 0 1 0 0 0 0 0 6 3 13 12 0 4 58
F12b corporate
downsizing
0.27 -0.72 0.95 4.92* 1.08 -1.41 -1.59 -1.06 -1.35 -1.24 0.68 -1.02 3.59* 4.48* 6.85* 4.97* -1.29 -0.67 -0.86
1 6 4 0 3 0 0 1 1 1 2 1 4 0 1 12 1 12 50
0 8 4 0 5 0 3 1 1 1 1 1 3 0 0 15 1 15 59
F13 malignant
tumor
-1.25 2.73* 2.81* -1.35 0.79 -1.40 -0.65 0.41 -0.17 -1.21 1.42 -0.42 3.25* -0.51 -1.22 5.70* -0.05 5.01* -0.99
Selectional Restrictions 50
3 3 0 0 6 0 4 2 5 1 0 0 0 0 1 7 15 4 51
3 4 0 0 4 0 5 0 6 2 0 0 0 0 0 8 12 9 53
F14 sleepiness
1.71 1.04 -1.15 -1.17 2.00* -1.22 2.28* 0.77 4.27* -0.31 -0.73 -1.27 -0.82 -0.33 -0.90 3.52* 8.01* 2.49* -1.87
2 4 4 1 5 0 0 2 4 2 2 2 3 2 2 2 5 6 48
3 8 2 1 6 1 1 2 4 2 1 1 5 0 1 3 10 7 58
F15 sense of
foreboding
-0.21 0.88 1.00 -0.94 0.51 -1.50 -2.17* 0.85 1.82 -1.28 0.64 -0.69 2.75* 0.81 -1.01 -1.34 4.39* 0.64 2.22*
65 71 64 65 86 80 80 46 57 94 44 63 57 30 70 80 52 85 1189
63 94 52 59 120 80 98 44 68 98 34 61 51 26 50 95 49 115 1257
Total
1.12 5.42* -0.88 -0.79 5.33* -0.41 2.75* -2.60* -0.89 3.17* -3.29* -0.11 -2.51* -4.66* 1.01 5.79* -1.35 6.81*
Note. In each cell, the first line shows the number of participants who chose the item in the active form condition, and
the second line shows the number of those that chose it in the passive form condition. The third line presents the
standardized estimated parameters. The asterisks in the third line indicate that p < .05.
Selectional Restrictions 51
Table 4.
A summary of the hierarchical deletion steps involved in arriving at the final
model
Step Model df G2 p Term
deleted
∆df ∆G2 ∆p
1 (V, Sub) (V, Obj) (Sub, Obj) 289 145.21 1.00
(V, Obj) 17 21.57 0.20
2 (V, Sub) (Sub, Obj) 306 166.79 1.00
(V, Sub) 17 22.63 0.16
3 (Sub, Obj) (V) 323 189.42 1.00
(V) 1 1.89 0.17
4 (Sub, Obj) 324 191.31 1.00
Selectional Restrictions 52
Table 5.
Choice frequency of each object NP as a function of subject NPs given in sentences (Experiment 2)
Subject NPs embedded in the sentences
F01A
mob
F01B
two
ruff
ians
F02
coun
try w
ith fe
w re
sorc
es
F03
thre
e m
en
F04
stal
ker
F05A
dru
g ad
dict
F05B
mur
dere
r
F06
lions
F07
wild
boa
r
F08
truck
out
of c
ontro
l
F09
larg
e ty
phoo
n
F10
land
slid
es
F11
new
type
of p
neum
onia
F12A
stoc
k cr
ash
F12B
cor
pora
te d
owns
izin
g
F13
mal
igna
nt tu
mor
F14
slee
pine
ss
F15
sens
e of
fore
bodi
ng
Total
F01a 15 4 2 5 0 3 2 1 5 4 2 4 1 0 3 1 3 6 61
0.09 1.04 0.41 -0.92 0.17 -0.73 1.05 -1.08 0.03 0.29 0.24 0.63 -0.17 -0.14 -0.16 -0.95 -0.76 -0.13 -0.45
13 1 1 7 0 3 0 6 4 2 3 2 1 0 3 2 7 8 63
squad of police
-0.09 -1.04 -0.41 0.92 -0.17 0.73 -1.05 1.08 -0.03 -0.29 -0.24 -0.63 0.17 0.14 0.16 0.95 0.76 0.13 0.45
Selectional Restrictions 53
5.98* -0.54 0.68 1.25 -0.99 0.07 -0.82 -0.31 0.67 -0.01 -0.74 -0.90 -1.36 -1.27 1.86 0.07 2.09* 2.00* -0.37
F01b 10 10 3 11 4 10 3 4 3 4 1 2 5 2 1 12 6 9 100
-0.26 0.40 0.47 0.42 0.14 0.13 -0.57 0.49 -0.72 -0.65 0.64 -0.38 -0.83 0.41 -0.88 0.18 0.01 1.16 -0.21
12 8 2 8 6 6 5 6 5 5 1 3 8 1 3 8 9 7 103
0.26 -0.40 -0.47 -0.42 -0.14 -0.13 0.57 -0.49 0.72 0.65 -0.64 0.38 0.83 -0.41 0.88 -0.18 -0.01 -1.16 0.21
statesman
2.37* 1.65 0.35 0.75 2.55* 0.97 0.44 -0.68 -1.58 -0.73 -3.02* -2.83* 0.55 -0.87 -0.68 4.13* 1.86 0.24 6.87*
F02 1 0 13 0 0 0 0 0 0 0 15 2 14 11 1 2 0 1 60
0.56 -0.16 -0.87 -0.22 0.09 -0.39 -0.13 -0.48 -0.18 -0.28 0.86 -0.71 0.55 0.77 0.54 0.70 0.05 0.04 0.73
0 0 17 0 0 0 0 1 0 0 14 3 7 4 0 0 0 1 47
-0.56 0.16 0.87 0.22 -0.09 0.39 0.13 0.48 0.18 0.28 -0.86 0.71 -0.55 -0.77 -0.54 -0.70 -0.05 -0.04 -0.73
small country in
the Middle East
-0.90 -1.28 10.77* -1.60 -0.20 -1.31 -0.73 -0.92 -1.49 -1.30 7.94* 0.60 6.52* 6.37* 0.07 0.28 -0.97 -0.59 -4.27*
F03 12 4 1 14 0 10 0 0 1 9 1 1 1 11 12 1 0 1 79
0.38 0.29 -0.80 0.39 0.06 1.37 -0.16 -0.90 0.48 1.05 -0.19 -1.24 0.47 -1.33 -0.28 0.30 0.02 0.00 1.07
7 2 2 7 0 1 0 2 0 2 2 3 0 15 10 0 0 1 54
bank in Tokyo
-0.38 -0.29 0.80 -0.39 -0.06 -1.37 0.16 0.90 -0.48 -1.05 0.19 1.24 -0.47 1.33 0.28 -0.30 -0.02 0.00 -1.07
Selectional Restrictions 54
4.52* 0.63 1.15 4.05* -0.72 0.91 -1.26 -1.29 -1.72 1.66 -0.97 -1.04 -1.39 8.36* 7.58* -0.70 -1.50 -1.48 -1.97*
F04 5 18 1 18 20 16 20 7 4 9 1 2 6 1 10 10 12 13 173
-0.81 0.10 0.87 -0.24 1.09 -1.12 0.24 0.95 -1.60 -0.69 -0.76 -0.83 -1.03 0.76 0.50 -0.78 0.80 0.44 -1.09
10 20 0 21 22 20 22 10 12 12 6 5 12 0 9 13 14 18 226
0.81 -0.10 -0.87 0.24 -1.09 1.12 -0.24 -0.95 1.60 0.69 0.76 0.83 1.03 -0.76 -0.50 0.78 -0.80 -0.44 1.09
woman living
alone
-1.21 3.19* -2.09* 2.05* 7.35* 2.75* 5.53* -0.75 -1.66 0.31 -3.17* -3.74* -0.17 -2.28* 2.52* 2.98* 2.43* 1.03 12.28*
F05a 6 16 0 16 2 17 20 8 14 14 1 15 0 0 0 0 1 2 132
-0.53 0.86 0.15 0.15 0.76 -0.52 0.97 1.12 0.41 -0.24 -0.83 1.98 -1.27 0.07 0.13 -0.04 -0.25 -0.92 -1.01
11 13 0 17 2 18 16 11 14 16 7 7 3 0 0 0 3 8 146
0.53 -0.86 -0.15 -0.15 -0.76 0.52 -0.97 -1.12 -0.41 0.24 0.83 -1.98 1.27 -0.07 -0.13 0.04 0.25 0.92 1.01
pedestrians
1.78 4.50* -1.55 4.13* 0.67 5.37* 7.10* 2.33* 3.73* 4.70* -1.33 1.69 -1.82 -1.71 -1.78 -1.89 -1.03 -0.91 2.76*
F05b 6 13 0 15 1 17 17 11 14 15 1 12 6 0 0 3 7 1 139
-0.64 0.84 0.12 -0.35 -0.22 -0.39 0.23 1.42 0.62 -0.22 -0.29 1.24 -0.80 0.04 0.10 0.26 0.56 -1.72 -0.92
11 10 0 19 3 16 19 13 12 16 4 8 11 0 0 2 9 10 163
primary school
students
0.64 -0.84 -0.12 0.35 0.22 0.39 -0.23 -1.42 -0.62 0.22 0.29 -1.24 0.80 -0.04 -0.10 -0.26 -0.56 1.72 0.92
Selectional Restrictions 55
0.93 2.52* -1.82 3.31* -0.05 4.20* 6.37* 2.53* 2.44* 4.00* -2.40* 0.56 1.35 -1.98* -2.05* -0.45 2.02* -1.73 5.27*
F06 1 0 1 1 0 2 0 17 6 3 1 1 2 0 0 1 0 1 37
0.65 -0.09 -0.10 -0.24 0.16 0.72 -0.06 1.01 -0.75 0.49 -0.88 -1.03 0.98 -0.15 -0.08 0.42 -0.96 -0.70 0.38
0 0 1 1 0 0 0 17 8 1 5 3 0 0 0 0 2 3 41
-0.65 0.09 0.10 0.24 -0.16 -0.72 0.06 -1.01 0.75 -0.49 0.88 1.03 -0.98 0.15 0.08 -0.42 0.96 0.70 -0.38
herd of impalas
-0.94 -1.31 1.39 -0.69 -0.22 -0.58 -0.76 9.09* 4.29* 0.65 0.83 -0.06 -0.47 -0.51 -0.57 -0.10 -0.15 0.16 -4.43*
F07 1 4 0 8 0 2 2 5 17 1 5 20 5 0 0 1 10 12 93
-0.61 -0.65 0.15 0.96 -0.88 -0.98 -0.06 0.29 0.21 0.02 0.81 1.04 0.92 0.07 0.14 -1.50 1.13 1.55 -1.07
3 8 0 5 3 4 3 11 19 1 8 17 3 0 0 5 10 10 110
0.61 0.65 -0.15 -0.96 0.88 0.98 0.06 -0.29 -0.21 -0.02 -0.81 -1.04 -0.92 -0.07 -0.14 1.50 -1.13 -1.55 1.07
mountain hiker
-1.44 1.21 -1.37 0.67 -0.24 -0.65 0.34 1.97* 5.80* -1.93 1.06 5.54* 0.27 -1.53 -1.60 0.42 4.39* 3.09* 1.5596
F08 5 14 0 14 0 18 17 10 15 13 1 10 1 0 0 1 6 5 130
-0.87 0.05 0.08 -0.41 -0.73 -0.30 0.29 1.33 0.00 -0.92 -0.37 0.91 -1.15 -0.01 0.06 0.60 1.56 0.22 -0.52
10 15 0 17 2 15 17 11 16 18 4 7 4 0 0 0 3 7 146
mother and her son
0.87 -0.05 -0.08 0.41 0.73 0.30 -0.29 -1.33 0.00 0.92 0.37 -0.91 1.15 0.01 -0.06 -0.60 -1.56 -0.22 0.52
Selectional Restrictions 56
1.08 4.36* -1.61 3.60* -0.77 4.87* 6.70* 2.64* 4.05* 4.63* -1.97* 0.67 -1.42 -1.77 -1.84 -1.63 0.55 -0.16 3.29*
F09 0 0 2 0 0 0 0 1 2 1 19 6 10 0 2 3 0 1 47
-0.10 -0.89 -0.92 -0.18 0.12 -0.36 -0.10 0.39 0.93 0.43 0.61 -0.05 0.87 -0.19 -0.24 1.00 -0.63 0.10 0.59
0 1 4 0 0 0 0 1 0 0 22 5 4 0 2 0 1 1 41
0.10 0.89 0.92 0.18 -0.12 0.36 0.10 -0.39 -0.93 -0.43 -0.61 0.05 -0.87 0.19 0.24 -1.00 0.63 -0.10 -0.59
Kyusyu area
-1.36 -0.84 3.79* -1.60 -0.21 -1.32 -0.74 -0.28 -0.78 -0.85 9.99* 2.96* 4.58* -0.49 2.39* 0.52 -0.45 -0.60 -4.41*
F10 5 8 0 12 0 7 0 3 12 15 7 13 1 0 0 0 0 0 83
0.24 0.45 -0.15 1.27 0.07 0.97 -0.15 0.44 0.50 0.83 -0.15 -0.58 0.49 -0.24 -0.17 -0.34 0.03 -1.39 0.91
3 4 0 3 0 1 0 3 6 5 11 13 0 0 0 0 0 3 52
-0.24 -0.45 0.15 -1.27 -0.07 -0.97 0.15 -0.44 -0.50 -0.83 0.15 0.58 -0.49 0.24 0.17 0.34 -0.03 1.39 -0.91
house
1.54 2.91* -0.73 2.24* -0.61 0.72 -1.14 0.82 3.96* 4.51* 4.28* 5.59* -1.25 -0.89 -0.96 -1.07 -1.38 -1.19 -2.40*
F11 0 0 8 0 0 0 0 0 2 0 16 1 16 14 2 1 0 5 65
0.01 -0.02 -1.28 -0.07 0.23 -0.24 0.01 -0.31 0.44 -0.13 1.08 -0.51 0.88 1.05 0.48 -0.82 -0.49 1.41 -0.01
0 0 18 0 0 0 0 1 1 0 18 2 9 6 1 2 1 2 61
Asian countries
-0.01 0.02 1.28 0.07 -0.23 0.24 -0.01 0.31 -0.44 0.13 -1.08 0.51 -0.88 -1.05 -0.48 0.82 0.49 -1.41 0.01
Selectional Restrictions 57
-1.57 -1.51 9.18* -1.82 -0.42 -1.54 -0.95 -1.19 -0.41 -1.52 8.27* -0.76 6.93* 7.32* 1.27 1.08 -0.71 0.97 -3.39*
F12a 3 0 1 1 0 2 0 0 0 1 1 2 0 19 2 1 0 4 37
0.76 -0.10 -1.27 -0.25 0.16 0.71 -0.07 -0.40 -0.11 -0.35 -0.01 0.38 -0.12 -0.59 -0.17 0.42 0.12 0.57 0.41
1 0 4 1 0 0 0 1 0 1 2 1 0 20 2 0 0 3 36
-0.76 0.10 1.27 0.25 -0.16 -0.71 0.07 0.40 0.11 0.35 0.01 -0.38 0.12 0.59 0.17 -0.42 -0.12 -0.57 -0.41
market
0.66 -1.26 2.88* -0.60 -0.17 -0.51 -0.70 -0.89 -1.46 -0.11 0.06 -0.29 -1.19 11.80* 2.48* -0.03 -0.94 1.82 -4.71*
F12b 8 2 2 5 0 3 0 0 1 7 2 5 1 9 12 0 0 1 58
0.95 -0.33 0.27 0.52 0.09 0.89 -0.13 -0.86 -0.30 0.37 -0.53 0.29 0.51 -1.27 -0.49 -0.32 0.05 0.05 0.86
3 2 1 2 0 0 0 2 1 3 5 3 0 13 12 0 0 1 48
-0.95 0.33 -0.27 -0.52 -0.09 -0.89 0.13 0.86 0.30 -0.37 0.53 -0.29 -0.51 1.27 0.49 0.32 -0.05 -0.05 -0.86
transport company
2.28* 0.12 1.34 0.43 -0.61 -0.87 -1.15 -1.16 -1.17 2.19* 0.71 0.76 -1.26 7.81* 8.33* -1.07 -1.39 -1.30 -2.58*
F13 2 11 0 13 5 14 12 4 7 10 2 5 8 1 14 16 15 8 147
-1.64 1.09 0.11 0.28 -0.21 -0.43 1.07 0.30 -0.24 -0.33 0.31 0.63 -0.88 -0.47 0.63 -0.69 0.77 0.06 -1.06
9 7 0 12 11 13 8 8 9 11 4 4 14 2 12 19 18 13 174
man in his prime
1.64 -1.09 -0.11 -0.28 0.21 0.43 -1.07 -0.30 0.24 0.33 -0.31 -0.63 0.88 0.47 -0.63 0.69 -0.77 -0.06 1.06
Selectional Restrictions 58
-1.84 0.25 -2.17* 0.53 2.97* 1.97* 2.48* -1.40 -0.82 0.92 -3.03* -2.98* 1.24 -1.55 4.48* 5.69* 4.18* -0.18 10.69*
F14 1 1 0 1 0 1 0 2 7 0 3 13 4 0 0 1 12 13 59
-0.19 -0.61 0.18 -0.34 -0.60 -0.66 -0.51 0.20 0.00 0.03 0.96 0.80 -0.21 0.09 0.16 -0.02 1.21 1.72 -1.06
2 3 0 2 2 2 1 5 9 0 4 12 6 0 0 1 12 10 71
0.19 0.61 -0.18 0.34 0.60 0.66 0.51 -0.20 0.00 -0.03 -0.96 -0.80 0.21 -0.09 -0.16 0.02 -1.21 -1.72 1.06
climber lost in the
moutain in winter
-0.78 -0.34 -0.87 -1.23 0.16 -0.71 -0.83 0.65 3.39* -1.86 0.60 5.09* 2.29* -1.03 -1.10 -0.01 6.73* 4.94* -1.80
F15 10 12 2 14 4 12 8 7 3 6 1 3 6 9 1 16 8 13 135
0.28 0.35 0.66 0.69 0.06 -0.88 -0.47 1.42 -0.87 -0.49 -0.10 0.18 -0.82 0.61 -0.80 -0.46 -0.13 1.19 -0.80
10 11 1 10 7 13 12 7 6 7 3 3 10 6 3 16 14 12 151
-0.28 -0.35 -0.66 -0.69 -0.06 0.88 0.47 -1.42 0.87 0.49 0.10 -0.18 0.82 -0.61 0.80 0.46 0.13 -1.19 0.80
effective manager
0.68 1.51 -1.19 0.44 1.90 1.78 2.64* -0.70 -2.31* -0.72 -3.29* -3.48* 0.15 2.27* -1.33 5.46* 2.23* 0.87 11.66*
Total 91 117 36 148 36 134 101 80 113 112 80 117 87 77 60 70 80 96 1635
0.15 0.35 0.11 0.78 -1.05 1.88 0.11 -2.50* 0.50 1.18 -3.04* 0.27 0.49 0.55 0.21 1.23 -1.00 -1.31 -0.75
105 105 51 132 58 112 103 116 122 100 123 101 92 67 57 68 103 118 1733
-0.15 -0.35 -0.11 -0.78 1.05 -1.88 -0.11 2.50* -0.50 -1.18 3.04* -0.27 -0.49 -0.55 -0.21 -1.23 1.00 1.31 0.75
Selectional Restrictions 59
2.01* 1.39 -4.20* 3.97* -4.48* 1.58 -1.91 2.19* 3.11* 1.55 3.72* 6.15* 0.98 -3.18* -3.05* -2.54* -0.69 4.38*
Note. In each cell, the first and the third lines (in bold) show the number of participants who chose the item in the
active and passive form conditions, respectively. The second and the fourth lines (italicized) show the standardized
effects for the active and the passive forms, respectively. The fifth line also shows the standardized effects, collapsing
the effect of the grammatical form. The asterisks in the second, fourth, and fifth lines indicate that p < .05.
Selectional Restrictions 60
Table 6 Fitness index of the selected model (Experiment 2)
Step Model df G2 p Term deleted
∆df ∆G2 ∆p
1 (V, Sub) (V, Obj) (Sub, Obj) 289 198.18 1 (V, Sub) 17 44.64 0.0003
Selectional Restrictions 61
Figure Caption Figure 1. Two-dimensional correspondence map of the subject NP choices (Experiment 1). The proximity of the words on the map reflects their contingency.
Selectional Restrictions 62
House
Transport company
Market
Asian countries
Kyusyu area
Corporate downsizing
Large typhoon
Squad of police
Mother andher son Primary school students
Pedestrians
Mountain hiker
Climber lost in themountain in winter
Man in his primeEffective manager
Statesman
Impalas
Bank in Tokyo
Small countryin the Middle East
Three men
Mob
Two ruffiansStalker
Murderer
Drug addict
Lions
Wild boar
Stock crash
Country withfew resources
Truck out of control Malignant tumor
New type of pneumonia
Sleepiness
Sense of foreboding
Landslide
Subject NP
Object NP
-1.5
-1.0
-0.5
0.0
0.5
1.0
1.5
2.0
-1.0 -0.5 0.0 0.5 1.0 1.5 2.0Dim 1
Dim
2
Selectional Restrictions 63
Figure Caption Figure 2. Two-dimensional correspondence map of the object NP choices (Experiment 2). The proximity of the words on the map reflects their contingency.
Selectional Restrictions 64
Transport company
Market
Kyusyu area
Large typhoon
Object NP
Squad of police
Mother and her son
Primary schoolstudents
Pedestrians
Mountain hikerClimber lost in themountain in winter
Man in his primeEffective managerStatesman
Impalas
House
Bank in Tokyo
Asian countries
Small country inthe Middle East
Three men
Mob
Two ruffiansStalker
Murderer
Drug addict
LionsWild boar
Stock crash
Country withfew resorces
Corporate downsizing
Truck outof control Malignant tumor
New type of pneumonia
SleepinessSense of foreboding
Landslide
Subject NP
-1.5
-1.0
-0.5
0.0
0.5
1.0
1.5
-1.0 -0.5 0.0 0.5 1.0 1.5 2.0 2.5Dim 1
Dim
2
(Choice Item)
(Embedded in sentences)