Word sense disambiguation of WordNet glosses

Intelligent Database Systems Lab

N.Y.U.S.T.

I. M.

Word sense disambiguation of WordNet glosses

Presenter: Chun-Ping Wu　Author: Dan Moldovan, Adrian Novischi

Computer Speech and Language, 2004

國立雲林科技大學National Yunlin University of Science and Technology

2011/02/10

Intelligent Database Systems Lab

N.Y.U.S.T.

I. M.Outline Motivation Objective WordNet Methodology Experiments Conclusion Comments

2

Intelligent Database Systems Lab

N.Y.U.S.T.

I. M.Motivation

Manual disambiguation is known to be very laborious and time intensive.

It’s difficult to obtain a semantically tagged corpus and the features appearing in such corpus are very sparse, machine learning techniques were not found to be very successful.

3

This is my watch.(手錶 ?注視 ?)

Intelligent Database Systems Lab

N.Y.U.S.T.

I. M.Objective To present a suite of methods and results for the semantic

disambiguation of WordNet glosses.

4

This is my watch.(手錶 )

Intelligent Database Systems Lab

N.Y.U.S.T.

I. M.WordNet

WordNet Noun

ISA relation Verb

Change, communication, cognition, creation, emotion, etc.

Adjective Synonym/Antonym

Adverb Synonym/Antonym

5

gloss

Intelligent Database Systems Lab

N.Y.U.S.T.

I. M.Methodology Semantic disambiguation methods

Monosemous words Same hierarchy relation Lexical parallelism SemCor bigrams Cross-reference Reversed cross-reference Distance among glosses Common domain Patterns First sense restricted Building the WSD system using the methods

6

Intelligent Database Systems Lab

N.Y.U.S.T.

I. M.Methodology Monosemous words

Same hierarchy relation

7

Intelligent Database Systems Lab

N.Y.U.S.T.

I. M.Methodology Lexical parallelism

SemCor bigrams

8

Intelligent Database Systems Lab

N.Y.U.S.T.

I. M.Methodology Cross-reference

Reversed cross-reference

9

Intelligent Database Systems Lab

N.Y.U.S.T.

I. M.Methodology Distance among glosses

Common domain

10

Intelligent Database Systems Lab

N.Y.U.S.T.

I. M.Methodology Patterns

11

Intelligent Database Systems Lab

N.Y.U.S.T.

I. M.Methodology First sense restricted

A sense of noun or verb is more general if it has the smallest number of ancestors from all senses in the ISA hierarchy.

A sense of an adjective is more general if it has the largest number of similarity pointers from all senses.

Building the WSD system using the methods XWN_WSD

12

Intelligent Database Systems Lab

N.Y.U.S.T.

I. M.Experiments

Contribution of each method

13

Intelligent Database Systems Lab

N.Y.U.S.T.

I. M.Experiments

14

Voting

Intelligent Database Systems Lab

N.Y.U.S.T.

I. M.Conclusion

1515

A suite of heuristical methods are presented for the disambiguation of WordNet glosses.

Once the WordNet glosses are disambiguated, several applications become possible. QA System

Intelligent Database Systems Lab

N.Y.U.S.T.

I. M.Comments

1616

Advantage Many samples

Drawback Some mistakes Without theoretical basis

Application WSD, QA System