LING 438/538 Computational Linguistics Sandiway Fong Lecture 29.

Slides:



Advertisements
Similar presentations
Using Link Grammar and WordNet on Fact Extraction for the Travel Domain.
Advertisements

LING 581: Advanced Computational Linguistics Lecture Notes April 19th.
Lexical Semantics and Word Senses Hongning Wang
Introduction to Ontologies ECE457 Applied Artificial Intelligence Spring 2007 Lecture #13.
Section 4: Language and Intelligence Overview Instructor: Sandiway Fong Department of Linguistics Department of Computer Science.
Computational Intelligence 696i Language Lecture 7 Sandiway Fong.
LING 581: Advanced Computational Linguistics Lecture Notes April 27th.
LING 581: Advanced Computational Linguistics Lecture Notes May 5th.
LING 581: Advanced Computational Linguistics Lecture Notes April 6th.
C SC 620 Advanced Topics in Natural Language Processing Sandiway Fong.
C SC 620 Advanced Topics in Natural Language Processing Lecture 8 2/12/04.
1/27 Semantics Going beyond syntax. 2/27 Semantics Relationship between surface form and meaning What is meaning? Lexical semantics Syntax and semantics.
Slide 1 EE3J2 Data Mining EE3J2 Data Mining Lecture 7 Topic Spotting & Query Expansion Martin Russell.
Computational Intelligence 696i Language Lecture 5 Sandiway Fong.
Computational Intelligence 696i Language Lecture 6 Sandiway Fong.
Semantic distance in WordNet: An experimental, application-oriented evaluation of five measures Presenter: Cosmin Adrian Bejan Alexander Budanitsky and.
Experiments on Using Semantic Distances Between Words in Image Caption Retrieval Presenter: Cosmin Adrian Bejan Alan F. Smeaton and Ian Quigley School.
June 19-21, 2006WMS'06, Chania, Crete1 Design and Evaluation of Semantic Similarity Measures for Concepts Stemming from the Same or Different Ontologies.
Structured lexicons and Lexical semantics Especially WordNet ® See D Jurafsky & JH Martin: Speech and Language Processing, Upper Saddle River NJ (2000):
Using resources WordNet and the BNC. WordNet: History 1985: a group of psychologists and linguists start to develop a “lexical database” –Princeton University.
LING 388: Language and Computers Sandiway Fong Lecture 23: 11/15.
Designing clustering methods for ontology building: The Mo’K workbench Authors: Gilles Bisson, Claire Nédellec and Dolores Cañamero Presenter: Ovidiu Fortu.
C SC 620 Advanced Topics in Natural Language Processing Lecture Notes 2 1/20/04.
Article by: Feiyu Xu, Daniela Kurz, Jakub Piskorski, Sven Schmeier Article Summary by Mark Vickers.
LING 438/538 Computational Linguistics Sandiway Fong Lecture 25: 11/29.
C SC 620 Advanced Topics in Natural Language Processing Lecture Notes 3 1/22/04.
LING 581: Advanced Computational Linguistics Lecture Notes April 12th.
Antonym Creation Tool Presented By Thapar University WordNet Development Team.
WORDNET Approach on word sense techniques - AKILAN VELMURUGAN.
BT Exact Technologies - Adastral Park, Ipswich July - October 2003 Linguistic Web Services for Semantic Web Dr. Vassil T. Vassilev London Metropolitan.
Evaluating the Contribution of EuroWordNet and Word Sense Disambiguation to Cross-Language Information Retrieval Paul Clough 1 and Mark Stevenson 2 Department.
COMP423.  Query expansion  Two approaches ◦ Relevance feedback ◦ Thesaurus-based  Most Slides copied from ◦
“How much context do you need?” An experiment about context size in Interactive Cross-language Question Answering B. Navarro, L. Moreno-Monteagudo, E.
LING 388: Language and Computers Sandiway Fong Lecture 24: 11/17.
Intelligent Systems Lecture 20 Examples of NLP in searching systems.
Jennie Ning Zheng Linda Melchor Ferhat Omur. Contents Introduction WordNet Application – WordNet Data Structure - WordNet FrameNet Application – FrameNet.
1 Query Operations Relevance Feedback & Query Expansion.
WORD SENSE DISAMBIGUATION STUDY ON WORD NET ONTOLOGY Akilan Velmurugan Computer Networks – CS 790G.
WORDNET. THE WORDNET SYSTEM  Lexicographer files  Code: Lexico files  database  Search Routines and Interfaces.
10/22/2015ACM WIDM'20051 Semantic Similarity Methods in WordNet and Their Application to Information Retrieval on the Web Giannis Varelas Epimenidis Voutsakis.
Application of INTEX in refinement and validation of Serbian WordNet Ivan Obradović, Ranka Stanković Cvetana Krstev, Gordana Pavlović-Lažetić University.
WordNet: Connecting words and concepts Christiane Fellbaum Cognitive Science Laboratory Princeton University.
WordNet: Connecting words and concepts Peng.Huang.
11 Chapter 19 Lexical Semantics. 2 Lexical Ambiguity Most words in natural languages have multiple possible meanings. –“pen” (noun) The dog is in the.
Wordnet - A lexical database for the English Language.
WordNet Enhancements: Toward Version 2.0 WordNet Connectivity Derivational Connections Disambiguated Definitions Topical Connections.
Lecture 19 Word Meanings II Topics Description Logic III Overview of MeaningReadings: Text Chapter 189NLTK book Chapter 10 March 27, 2013 CSCE 771 Natural.
Knowledge Structure Vijay Meena ( ) Gaurav Meena ( )
2/10/2016Semantic Similarity1 Semantic Similarity Methods in WordNet and Their Application to Information Retrieval on the Web Giannis Varelas Epimenidis.
TUNING HIERARCHIES IN PRINCETON WORDNET AHTI LOHK | CHRISTIANE D. FELLBAUM | LEO VÕHANDU THE 8TH MEETING OF THE GLOBAL WORDNET CONFERENCE IN BUCHAREST.
Lexical Semantics and Word Senses Hongning Wang
Detecting and Exploiting Figurative Language in WordNet Wim Peters Department of Computer Science University of Sheffield.
Sentiment Analysis Using Common- Sense and Context Information Basant Agarwal 1,2, Namita Mittal 2, Pooja Bansal 2, and Sonal Garg 2 1 Department of Computer.
Query expansion COMP423. Menu Query expansion Two approaches Relevance feedback Thesaurus-based Most Slides copied from
Mapping the NCI Thesaurus and the Collaborative Inter-Lingual Index Amanda Hicks University of Florida HealthInsight Workshop, Oslo, Norway.
Lexicons, Concept Networks, and Ontologies
LING 581: Advanced Computational Linguistics
ArtsSemNet: From Bilingual Dictionary To Bilingual Semantic Network
Nouns Nouns not noun noun noun not not
LING 581: Advanced Computational Linguistics
CSC 594 Topics in AI – Applied Natural Language Processing
LING 581: Advanced Computational Linguistics
WordNet: A Lexical Database for English
Introduction to Ontologies
Bulgarian WordNet Svetla Koeva Institute for Bulgarian Language
WordNet WordNet, WSD.
CS 620 Class Presentation Using WordNet to Improve User Modelling in a Web Document Recommender System Using WordNet to Improve User Modelling in a Web.
Lecture 19 Word Meanings II
Giannis Varelas Epimenidis Voutsakis Paraskevi Raftopoulou
LING/C SC 581: Advanced Computational Linguistics
Presentation transcript:

LING 438/538 Computational Linguistics Sandiway Fong Lecture 29

Administrivia Homework –Homework 4, I’ll back tomorrow –Homework 5 due tonight Reminder –538 Presentations on Wednesday slides due Tuesday night

New Topic Semantic Inference and Language –A step outside syntax let’s look at computation using –WordNet project led by a psychologist –George Miller (Princeton University) handbuilt network of synonym sets (synsets) with semantic relations connecting them very popular in computational linguistics

WordNet what is it? –synonym set (synset) network for nouns, verbs, adjectives and adverbs –synsets connected by semantic relations (isa, antonymy,...) –139,000 entries (word senses) –10,000 verbs (polysemy 2), 20,000 adjectives (1.5) –originally conceived as a model of human semantic memory

WordNet what is it? –synonym set (synset) network for nouns, verbs, adjectives and adverbs –synsets connected by semantic relations (isa, antonymy,...) –139,000 entries (word senses), 10,000 verbs (polysemy 2), 20,000 adjectives (1.5) –originally conceived as a model of human semantic memory

WordNet what is it? –synonym set (synset) network for nouns, verbs, adjectives and adverbs –synsets connected by semantic relations (isa, antonymy,...) –139,000 entries (word senses), 10,000 verbs (polysemy 2), 20,000 adjectives (1.5) –originally conceived as a model of human semantic memory

WordNet extremely popular resource for language applications –freely available (project cost $3M) –many Wordnets based on the Princeton system have been proposed or built for other languages EuroWordNet (EWN) ItalWordNet Tamil WordNet Estonian WordNet

WordNet Applications examples –information retrieval and extraction query term expansion (synonyms etc.) cross-linguistic information retrieval (multilingual WordNet) –concept identification in natural language word sense disambiguation WordNet senses and ontology (isa-hierarchy) –semantic distance computation relatedness of words –document structuring and categorization determine genre of a paper (WordNet verb categories)

Using WordNet Online URL: current version: 3.0

WordNet Relations RelationDescriptionExample x HYP yx is a hypernym of yx: repair, y: improve x ENT yx entails yx: breathe, y: inhale x SIM yy is similar to x (A)x: achromatic, y: white x CS yy is a cause of xx: anesthetize, y: sleep x VGP yy is similar to x (V)x: behave, y: pretend x ANT yx and y are antonymsx: present, y: absent x SA yx, see also yx: breathe, y: breathe out x PPL yx participle of yx: applied, y: apply x PER yx pertains to yx: abaxial, y: axial

Semantic Opposition Event-based Models of Change and Persistence in Language (Pustejovsky, 2000): –John mended the torn dress –John mended the red dress –what kind of knowledge is invoked here? from Artificial Intelligence (AI): –an instance of the frame problem –aka the update problem –computation: what changes in the world and what doesn’t?

Persistence and Change of State Verbs Event-based Models of Change and Persistence in Language (Pustejovsky, 2000): –John mended the torn dress –John mended the red dress Verb Classes: Aspectual Classes (Vendler 1967) –Mary cleaned the dirty tableChange of State –The waiter filled every empty glass –Mary fixed the flat tire –Bill swept the dirty floorActivity –Bill swept the dirty floor cleanAccomplishment –Nero built the gleaming templeCreation –Nero ruined the splendid templeDestruction

Event Representation Change of State Verbs: –John mended the torn/red dress –mend: x CAUS y BECOME –John CAUS the torn/red dress BECOME antonym relation between adjective and the end state

Using WordNet Online Let’s explore mend:

Using WordNet Online Let’s explore mend:

Using WordNet Online Let’s explore mend:

Using wnconnect A program on my homepage – connect/index.htmlhttp://dingo.sbs.arizona.edu/~sandiway/wn connect/index.html –written in 2003 (for a research paper) –uses an older version of WordNet (1.6) –graphs connections

Using wnconnect Find shortest link between mend and tear in WordNet:

Using wnconnect Find shortest link between mend and tear in WordNet: –mend/v is in [repair,mend,fix,bushel,doctor,furbish_up,restore,touch_on] –repair and break/v are antonyms –bust in [break,bust] and bust/v related by verb.contact –tear/v is in the synset [tear,rupture,snap,bust]

Using wnconnect two senses of bust: (1) to ruin completely, (2) to separate or cause to separate abruptly

Using wnconnect –John CAUS the red dress BECOME mend/n is in [mend,patch] [mend,patch] is an instance of [sewing,stitchery] [sewing,stitchery] is an instance of [needlework,needlecraft] [needlework,needlecraft] is an instance of [creation] [creation] is an instance of [artifact,artefact] [artifact,artefact] is an instance of [object,physical_object] [object,physical_object] is an instance of [entity,physical_thing] [causal_agent,cause,causal_agency] is an instance of [entity,physical_thing] [person,individual,someone,somebody,mortal,human,soul] is an instance of [causal_agent,cause,causal_agency] [disputant,controversialist] is an instance of [person,individual,someone,somebody,mortal,human,soul] [radical] is an instance of [disputant,controversialist] [Bolshevik,Marxist,pinko,red,bolshie] is an instance of [radical] red/n is in the synset [Bolshevik,Marxist,pinko,red,bolshie]

Using wnconnect –John CAUS the red dress BECOME

Shortest Path mend–tear all paths

Point of Discussion some issues –knowledge representation for semantic inferencing –do we have a network like WordNet? –how is it built? –is it wholly outside the “language faculty”?

Another Application Solving GRE word quiz drills

Another Application 65 quizzes –92% correct –remaining errors reveal gaps in WordNet’s lexical knowledge Some moribund code left…needs development: –Want to write a paper with me? –anyone want to take it up?...