october 2004csa3050 nlp algorithms1 csa3050: natural language algorithms morphological parsing

October 2004 CSA3050 NLP Algorithms 1

CSA3050: Natural Language Algorithms

Morphological Parsing

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Morphology

• Morphemes: The smallest unit in a word that bear some meaning, such as rabbit and s, are called morphemes.

• Combination of morphemes to form words that are legal in some language.

• Two kinds of morphology– Inflectional– Derivational

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Inflectional/DerivationalMorphology

• Inflectional+s plural+ed past

• category preserving• productive: always

applies (esp. new words, e.g. fax)

• systematic: same semantic effect

• Derivational+ment

• category changingescape+ment

• not completely productive: detractment*

• not completely systematic: apartment

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Noun Inflections

Regular Irregular

Singular cat church mouse ox

Plural cats churches mice oxen

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Morphological Parsing

MorphologicalParser

Input Word

cats

OutputAnalysis

cat N PL

• Output is a string of morphemes• Reversibility?

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Morphological Parsing

• The goal of morphological parsing is to find out what morphemes a given word is built from. mouse mouse N SGmice mouse N PLfoxes fox N PL

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2 Steps1. Split word up into its possible components,

using + to indicate possible morpheme boundaries.

cats cat + sfoxes fox + sfoxes foxe + s

2. Look up the categories of the stems and the meaning of the affixes, using a lexicon of stems and affixes

cat + s cat + NP + PLfox + s fox + N + PL.

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Step 1: Surface IntermediateFST

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Step 1: Surface IntermediateOperation

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2. Intermediate Morphemes

Possible inputs to the transducer are:

• Regular noun stem: cat• Regular noun stem + s: cat+s• Singular irregular noun stem: mouse• Plural irregular noun stem: mice

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2. Intermediate MorphemesTransducer

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Handling Stems

cat /cat

mice/mouse

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Completed Stage 2

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Joining Stages 1 and 2

• If the two transducers run in a cascade (i.e. we let the second transducer run on the output of the first one), we can do a morphological parse of (some) English noun phrases.

• We can change also the direction of translation (in translation mode).

• This transducer can also be used for generating a surface form from an underlying form.

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Prolog• The transducer

specifications we have seen translate easily into Prolog format except for the other transition.

• arc(1,3,z:z).arc(1,3,s:s).arc(1,3,x:x).arc(1,2,#:+).arc(1,3,<other>).

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Handling other arcs

arc(1,3,z:z) :- !.arc(1,3,s:s) :- !.arc(1,3,x:x) :- !.arc(1,2,#:+) :- !.arc(1,3,X:X) :- !.

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Combining Rules• Consider the word “berries”.• Two rules are involved

– berry + s– y → ie under certain circumstances.

• Combinations of such rules can be handled in two ways– Cascade, i.e. sequentially– Parallel

• Algorithms exist for combining transducers together in series or in parallel.

• Such algorithms involve computations over regular relations.

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3 Related Frameworks

REGULARLANGUAGES

REGULAREXPRESSIONS

FSA

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REGULAR RELATIONS

REGULARRELATIONS

AUGMENTEDREGULAR

EXPRESSIONS

FINITE STATETRANSDUCERS

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Putting it all together

execution of FSTi

takes place in parallel

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Kaplan and KayThe Xerox View

FSTi are alignedbut separate

FSTi intersectedtogether

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Summary

• Morphological processing can be handled by finite state machinery

• Finite State Transducers are formally very similar to Finite State Automata.

• They are formally equivalent to regular relations, i.e. sets of pairings of sentences of regular languages.