Interlingua Methodology

Directly obtain the meaning of the source sentence. Do target sentence generation from the meaning

representation. John gave the book to Mary.

Meaning representation: give-action: agent: john object: the book receiver: mary

Competing approaches

Direct

Transfer based

Direct approach

Word replacementsI like mangoesmaOM AcCa laga AamaI like (root) mangoes

MorphologymaOM AcCa lagata AamaI like mangoes

Syntactic re-arrangement maOM Aama AcCa lagata hO

I mangoes like Semantic embellishment

mauJao Aama AcCa lagata hOI (dative) mangoes like

Transfer BasedSource sentence processed for parsing, chunking etc.

SS

NPNPVPVP

VV NPNP

IIlikelike

mangoesmangoes

Transfer Based

Transfer structures obtained for the target sentence.

SS

NPNPVPVP

VV

IIlikelike

NPNP

mangoesmangoes

Transfer Based

Morphology and language specific modifications

SS

NPNPVPVP

VV

mauJaomauJaoAcCa lagataa hOAcCa lagataa hO

NPNP

AamaAama

MT Architectures: Vauquois' triangle

Deep understanding level

Interlingual le vel

Logico-semantic level

Syntactico-functio nal level

Morpho-syntac tic level

Syntagmatic level

Graphemic leve l Direct translation

Syntactic transfer (surface )

Syntactic transfer (deep)

Conceptual transfer

Semantic transfer

Multilevel transfer

Ontological interlingua

Semantico-linguistic interlingua

SPA-structures (semantic& predicate-argument)

F-structures (functional)

C-structures (constituent)

Tagged tex t

Text

Mixing levels Multilevel descriptio n

Semi-direct translatio n

Relation Between the Transfer and the Interlingua Models

Interpretation generation

transfer

Parsing generation

Interlingua

Source languageParse tree

Target LanguageParse tree

source languagewords

Target language words

State of Affairs

Systran reports 19 different language

pairs. 8 alright for intended use. Even fewer are capable of quality written

or spoken text translation.

ENGLISH-SPANISH-ENGLISH

...In that Empire, the Art of Cartography attained such Perfection that the map of a single Province occupied the entirety of a City, and the map of the Empire, the entirety of a Province

... en ese imperio, el arte de la cartografía logró tal perfección que el mapa de una sola provincia ocupó la totalidad de una ciudad, y el mapa del imperio, la totalidad de una provincia

... in that empire, the art of the cartography obtained such perfection that the map of a single province occupied the totality of a city, and the map of the empire, the totality of a province

Provided by Systran on 19/11/02

ENGLISH-KOREAN-ENGLISH

...In that Empire, the Art of Cartography attained such Perfection that the map of a single Province occupied the entirety of a City, and the map of the Empire, the entirety of a Province

저 제국안에 , 단순한 지방의 지도가 도시의 완전을 점유했다 고 Cartography 의 예술은 같은 얀벽 , 및 제국 , 지방의 완전의 지도 를 달성했다

Inside that empire, the map of the region where it is simple occupied the perfection of the city the art of the Cartography is same, yan it attained the map of of perfection of the wall and

empire and region

Provided by Systran on 19/11/02

UNL Based MT: the scenario

UNL

ENGLISH

HINDIFRENCH

RUSSIANENCONVERSION

DECONVERSION

Common language for computers to express

information written in natural language (Uchida et. al. 2000)

Application: Electronic language to overcome language barrier

Information Distribution System

Universal Networking Language

UNL Example

agt obj plc

arrangearrange

JohnJohn meetingmeeting residenceresidence

Components of the UNL System

Universal Word

Relation Labels

Attributes

Universal Word

[saayaa] "shadow(icl>darkness)"; the place was now in shadow

[laoSamaa~] "shadow(icl>iota)"; not a shadow of doubt about his guilt

[saMkot] "shadow(icl>hint)" ; the shadow of the things to come

[Cayaa] "shadow(icl>deterrant)"; a shadow over his happiness

Universal Word (foreign concepts)

[aput] "snow(icl>thing)";

[pukak] "snow(aoj<salt like)";

[mauja] "snow(aoj<soft, aoj<deep)";

[massak] "snow(aoj<soft)";

[mangokpok] "snow(aoj<watery)";

Relation

agt (agent) Agt defines a thing which initiates an action.agt (do, thing)Syntax

agt[":"<Compound UW-ID>] "(" {<UW1>|":"<Compound UW-ID>} "," {<UW2>|":"<Compound UW-ID>} ")"

Detailed DefinitionAgent is defined as the relation between:UW1 - do, andUW2 - a thingwhere:

UW2 initiates UW1, or

UW2 is thought of as having a direct role in making UW1 happen. Examples and readings

agt(break(icl>do), John(icl>person)) John breaksagt(translate(icl>do), computer(icl>machine)) computer translates

Attributes

Used to describe what is said from the speaker's point of view.

In particular captures number, tense, aspect and modality information.

Example Attributes

I see a flower UNL: obj(see(icl>do), flower(icl>thing))

I saw flowers UNL: obj(see(icl>do).@past, flower(icl>thing).@pl)

Did I see flowers? UNL: obj(see(icl>do).@past.@interrogative,

flower(icl>thing).@pl) Please see the flowers?

UNL: obj(see(icl>do).@past.@request, flower(icl>thing).@pl.@definite)

The Analyser Machine

EnconverterAnalysis

RulesDictionary

C CC A A

nini+1 ni+2Node List

A

B E

D

C

Node-net

ni-1 ni+3

Strategy for Analysis

Morphological Analysis

Syntactico-Semantic Analysis

Analysis of a simple sentences

<< A Report of John’s genius reached King’s ears>>

article and noun are combined and attribute@indef is added to the noun.

 

<<[Report ][of] John’s genius reached king’s ears>>

Right shift to put preposition with the succeeding noun.

 

<</Report /[of ][John’s] genius reached king’s ears>>

Ram’s being a possessing noun, shift right.

 

<</Report //of / [John’s] [genius] reached king’s ears>>

These two nouns are resolved into relation pos and first noun is deleted:

 

Simple sentence (continued)

<</Report /[of][genius] reached King’s ears>> The preposition of is then combined with noun and a dynamic attribute OFRES is added to entry of genius. <<[Report][of genius ] reached King’s ears>> Using the attribute OFRES these two nouns are resolved to relation mod and the second noun is deleted. <<[Report ][reached] King’s ears>> Shift right again and solve King’s ears, relation pof is generated.  

<</Report /[reached][ ears]>> Relation obj is generated here and then relation agt is generated between Report and ears <</reached />>

UNL as Interlingua and Language Divergence

(Dave, Parikh, Bhattacharyya, JMT, 2003)

Stands for the discrepancy in representation

due to the inherent characteristics of the

languages. Syntactic Divergence Lexical Semantic Divergence

Issue of free word order

 jaIma nao caaorI krnaovaalao laD,ko kao laazI sao maara.

jaIma nao laazI sao caaorI krnaovaalao laD,ko kao maara.

caaorI krnaovaalao laD,ko kao jaIma nao laazI sao maara.

caaorI krnaovaalao laD,ko kao laazI sao jaIma nao maara.

laazI sao jaIma nao caaorI krnaovaalao laD,ko kao maara.

Use made of the fact that in Hindi post positions stay adjacent to nouns (opposed to the preposition stranding divergence).

Flexibility in parsing- hit and preserve the predicate till the end.

Conjunct and Compound verbs

 Typical Indian language phenomenon. Conjunct for verb-verb, compound for other POS+verb.

vah gaanao lagaI She started singing

H calao jaaAaoE Go away.H $k jaaAao E Stop there.H Jauk jaaAaoE Bend down.

Possibility of combinatorial explosion in the lexicon. Possiblesolution: wordnet?

Use of Lexical Resources

Automatic Generation of the UW to language dictionary (Verma and Bhattacharyya, Global Wordnet Conference, Czeck Republic, 2004)

Universal Word generation Semantic attribute generation Heavy use of wordnets and ontologies

Languages under Study

Language Analysis Status Generation Status

English D- 60000

R- 5000

D- 60000

R- 400

Hindi D- 75000

R- 5700

D- 75000

R- 6500

Marathi D- 4000

R- 2200

D- 4000

R- 6000

Bengali D- 500

R- 1800

D- 500

R- 2100

Conclusions

Predicate preservation strategy used for

English, Hindi, Marathi, Bengali (Spanish

being added). Focus in marathi on morphology for

Marathi. Focus on kaarak (case) system for Bengali. Extremely lexical knowledge hungry.

Conclusions

Work going on in the creation of Indian language wordnets (Hindi, Marathi in IIT Bombay; Dravidian in Anna University).

Interlingua has a the attractive possibility of being used as a knowledge representation and applying to interesting applications like summarization, text clustering, meaning based multilingual search engines.

Generation of the Hindi Case System in an Interlingua based MT

Framework

Debasri Chakrabarti, Sunil Kumar Dubey, Pushpak Bhattacharyya.Computer Science and Engineering Department,

Indian Institute of Technology, Bombay,Mumbai, 400076, India.

debasri,dubey,pb@cse.iitb.ac.in

Introduction

Role of the case marker in a languageplays an important role in the structure of a sentencehelps to impart the meaning and naturalness

Example* मो�टे� तौ�र पर कृ षि� भू�मिमो कृ� जु�तौ�ई, फसलों� कृ� रुप�ई, कृटे�ई, प�लोंतौ� पशु� प्रजुनन, प�लोंन, दुग्ध- व्यवस�य और वन$कृरण सम्मि'मोलिलोंतौ हो�तौ� हो* । In a broad sense, agriculture includes cultivation of the soil and growing and harvesting crops and breeding and raising livestock and dairying and forestry.

The Case System in Hindi

Hindi is characterized by a rich subsystem of case

Example: र�मो न� रषिव कृ� षिकृतौ�ब दी/। Ram Erg Ravi Dat book Nom give + past Ram

gave a book to Ravi.

Hindi has the following cases nominative, ergative, accusative, instrumental, dative, genitive

locative

Language Universal Case Feature

Case ConditionsNominative

(NOM)case of the subjects. In a language if thereare two distinct cases for the subjects, oneinflected and the other without inflectionthen NOM refers to the uninflected one.

Ergative (ERG) the inflected case associated with the subject

Accusative (ACC) case attached with the object

Language Universal Case Feature

Case Conditions

Dative (DAT) case of goals/ recipients.

Instrumental (INS) case of instruments used to accomplish an action

Genitive (GEN) case of possessors

Locative (LOC) case of physical place

Case features of Hindi

Case Markers Conditions Example

1. Nominative Ө a. Subject र�मो आमो खा� रहो�था�।

b. Inanimate primary object

र�मो आमो खा�रहो� था�।

2. Ergative न� a. Agentive subject with perfective aspect

र�मो न� श्य�मो कृ�षिकृतौ�ब दी/ था$।

b. Simple past र�मो न� षिकृतौ�बपढ़ी/।

Case features of Hindi

Case Markers Conditions Example

3. Accusative कृ� a. Animate primary object र�मो न� स$तौ� कृ�दी�खा�।

b. Definite, Inanimate primary object

र�मो न� उस षिकृतौ�बकृ� पढ़ी�।

4. Dative कृ� Goal of the sentence र�मो न� स$तौ� कृ� षिकृतौ�ब दी/।

5. Ablative स� Source प�ड़ स� पत्ते� षि8र रहो�हो9।

Case features of Hindi

Case Markers Conditions Example

6. Instrumental स�

a. Instrumentर�मो न� चा�कृ� स� फलोंकृ�टे�।

b. Intermediary agent

[cause]

र�मो न� स$तौ� स� लिचाठ्ठी<लिलोंखाव�ई

c. Denoted agent of Passive

र�मो स� खा�न� नहो=खा�य� 8य�।

7. Genitive कृ�, कृ�, कृ�

a. Possessor [involving

ownershipof something]

र�मो कृ� षिकृतौ�ब अच्छी/हो*।

Case features of Hindi

Case Markers Conditions Example

7. Genitive कृ�, कृ�, कृ� b. Relationship to somebody

र�मो कृ� भू�ई अच्छी�हो*।

8. Locative मोD a. In, Within र�मो दिदील्लों$ मोD रहोतौ�हो*।

पर b. On, at र�मो प�ड़ पर चाढ़ी8य�।

Nominative ~ Ergative alternation in the agent position

agent of an action may bear either nominative case or ergative case

ergative case appears in Hindi simple past form perfective aspect

Examples

र�मो न� रषिव कृ� प$टे�। Ram erg Ravi acc beat+past Ram beat Ravi.

र�मो न� रषिव कृ� प$टे� था�। Ram erg Ravi acc beat+past perfect Ram had beaten Ravi.

र�मो न� रषिव कृ� प$टे� हो*। Ram erg Ravi acc beat+present perfect Ram has beaten Ravi.

Observations

There is a correlation between the ergative case and the aspectual property of the main verb

This is morphologically overt on the verb Simple Past Tense: प$टे� Perfective Aspect: प$टे� था�

Morphological Rule Simple Past Tense: V + आ न� Perfective Aspect: V + आ + (Tense morphology) न�

Nominative ~ Ergative Alternation

Some Complex Phenomena nominative case on the agent with the mentioned

aspectual features

IS nominative ~ ergative subject to transitivity?language universally transitivity determines nom

~ erg three types of patterns independent of transitivity

in Hindi

Nominative ~ Ergative Alternation

Three patterns are:only nom agentsonly erg agents either nom or erg agents

Examples of Intransitive verbs Only nom agents

i) र�मो षि8र�। Ram fell down

Ram +nom fall + past.

ii) *र�मो न� षि8र�। Ram erg f all + past

Intransitive Verbs

Only erg agents i) र�मो न� प्रतौ$क्षा� कृ�। Ram waited.

Ram erg wait + past. ii) * र�मो प्रतौ$क्षा� षिकृय�। Ram +nom wait + past.

Either nom or erg agents i) र�मो खा�लों�। Ram played. Ram +nom play + past. ii) र�मो न� खा�लों�। Ram erg play + past.

Transitive Verbs

Only nom agents i) र�मो शु$शु� लों�य�। Ram brought the glass.

Ram +nom glass bring + past.

ii) *र�मो न� शु$शु� लों�य�। Ram erg glass bring + past.

Only erg agents i) र�मो न� शु$शु� तौ�ड़�। Ram broke the glass.

Ram erg glass break + past.

ii) *र�मो शु$शु� तौ�ड़�। Ram +nom glass break + past.

Transitive Verbs

Either nom or erg agents

i) र�मो न� समोझा� षिकृ घर मो�र� हो*। Ram erg think + past that house mine is.

Ram thought that the house is mine. ii) र�मो समोझा� षिकृ घर मो�र� हो*। Ram think + past that house mine is.

Inferences

Ergative case in Hindi is semantically driven action performed deliberately : ergative case action performed non deliberately: nominative case

Examples of deliberate and non-deliberate action

र�मो षि8र�। Ram fell down

Ram +nom fall + past.

र�मो न� मो�होन कृ� षि8र�य�। Ram made Mohan to fall down.

Ram erg Mohan acc cause to fall down

Accusative ~ Nominative Alternation in the Object

Primary objects in Hindieither accusative : कृ� or nom uninflected : Ө

Examples र�मो न� चा�वलों खा�य�। Ram ate rice

Ram erg rice + nom eat+ past.

र�मो न� र�वण कृ� मो�र�। Ram killed Ravan.

Ram erg Ravan acc kill + past.

Accusative ~ Nominative Alternation

Generalizationanimate objects are accusative inanimate objects are nominative

Counter examples of this generalization accusative case with the inanimate objects र�मो न� षिकृतौ�ब कृ� उठा�य� । Ram lifted the book.

Ram erg book acc lift + past.

र�मो न� षिकृतौ�ब उठा�ई । Ram lifted a book. Ram erg book lift + past.

Summarization of the theoretical approach

NOM~ERG Alternationsubject to the semantic property of the verbthis semantic property conscious choice

NOM~ACC Alternationsubject to animacysubject to definiteness

How to generate the Case Markers in the UNL System

Three components to the generation system LexiconRule BaseUNL Expression

Lexiconattribute for a verb is taken from a verb hierarchy attribute of conscious choice is [DLBRT-ACT] [DLBRT-ACT] stands for deliberate action

Rule BaseHindi is a SOV languagea frequently used rule in Hindi is left insertion rulesa child node is mostly always inserted to the left of the

parent node given in the UNL expression

Format for the Rule :"<COND1>:<ACTION1>:<RELATION1>:<ROLE1>"{<COND2>:<ACTION2>:<

RELATION2>:<ROLE2>}

Case Markers in the UNL System

Sachin Rice

<<SHEAD>> eat@entry

G

agt obj

<<STAIL>>

G

Rice

<<SHEAD>> Sachin

G

obj

eat@entry

G

<<STAIL>><<SHEAD>> eat@entry <<STAIL>><<SHEAD>> सलिचान

Rice

obj

Rice

obj

खा�@entry

G GG G

<<STAIL>><<SHEAD>> eat@entry <<STAIL>><<SHEAD>> सलिचान

Rice

obj

Rice

obj

खा�@entry

G GG G

<<STAIL>><<SHEAD>> eat@entry <<STAIL>>सलिचान<<SHEAD>> खा�@entry

G GG G

<<STAIL>>चा�वलों<<SHEAD>> eat@entry <<STAIL>><<SHEAD>> सलिचान खा�@entry

G GG G

<<STAIL>>चा�वलों<<SHEAD>> eat@entry <<STAIL>><<SHEAD>> सलिचान खा�@entry

G GG G

<<STAIL>>चा�वलों<<SHEAD>> eat@entry <<STAIL>><<SHEAD>> सलिचान खा�@entry

G GG G

<<STAIL>>चा�वलों

Interpretation of a rule

Example of a left insertion rule:"<agt:+blk,+agt,+!ne,+sufc:agt:"{V,>agt,@past,DLBRT-ACT,^@progress:+!agt::}P242;

{} indicates parent node“ ” indicates child nodecondition of the parent node

V,>agt,@past,DLBRT-ACT,^@progress condition of the child node

<agt priority is denoted by P followed by a priority number

P242

Generation of the Case marker on the Agent

Rules for the generation system to handle the case of the agent

R1:"<agt:+blk,+agt,+!ne,+sufc:agt:"{V,>agt,@past,DLBRT-

ACT,^@progress:+!agt::}P242;

R2:"<agt:+blk,+agt,+sufc:agt:"{V,>agt,@past,^@progress:!agt::}P241;

Priority plays an important role in generationR1 Ergative R2 Nominative

Generation of the Case marker on the Object

Rules for the generation system to handle the case of the object

R5 :"<obj,INANI,MALE,^V,^SCOPE:+obj,+sufc,

+blk:obj:"{>obj:+!obj,+male::}P160;

R6 :"<obj,ANIMT,MALE,^V,^SCOPE:+obj,+sufc,+blk,+!

ko:obj:"{>obj:+!obj,+male::}P160;

R7 :"<obj,@def,MALE,^V,^SCOPE:+obj,+sufc,+blk,+!

ko:obj:"{>obj:+!obj,+male::}P163;

Conclusion

Resultprovides accuracy in the generation of case markers for the UNL

relations (see table) lends naturalness in the generation of the Hindi sentences This alternation is extended for the pronominal cases

Future Work enhance the study for Dative and Genitive case markers and their corresponding UNL relations

Demo