EnglishLexicalResources

Code for English lexical resources is located in "core" project. The actual resources code is in sub-packages of eu.excitementproject.eop.core.component.lexicalknowledge.

Distributional Similarity

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Resource name: Dekang Lin's dependency-based thesaurus

Implementation: LinDependencyOriginalLexicalResourse

Resource description: Resource was downloaded from Dekang Lin's website, http://webdocs.cs.ualberta.ca/~lindek/downloads.htm, but is not available there anymore. "Dependency-based thesaurus. This contains a list automatically constructed thesaurus. For each word, the thesaurus lists up to 200 most similar words and their similarities. The similar words are clustered (also automatically)."

POS: nouns (n), verbs (v), adjectives & adverbs (a)

Ref to relevant Paper: “Automatic Retrieval and Clustering of Similar Words”, Dekang Lin, COLING-ACL, 1998, pp. 768-774.

DB Scheme: lin (qa-srv:3308)

DB tables: lin_dep_n, lin_dep_v, lin_dep_a

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Resource name: Dekang Lin's proximity-based thesaurus

Implementation: LinProximityOriginalLexicalResource

Resource description: Resource is available for download from Dekang Lin's website, http://webdocs.cs.ualberta.ca/~lindek/downloads.htm. "Proximity-based thesaurus. Similar to the dependency-based thesaurus. But the words similarity is computed based on the linear proximity relationship between words only, where as the above thesaurus used dependency relationships extracted from a parsed corpus."

POS: nouns (n), verbs (v), adjectives & adverbs (a)

Ref to relevant Paper: “Automatic Retrieval and Clustering of Similar Words”, Dekang Lin, COLING-ACL, 1998, pp. 768-774.

DB Scheme: lin (qa-srv:3308)

DB tables: lin_proximity

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Resource name: Lin distributional similarity for Reuters

Implementation: LinDistsimLexicalResource

Resource description: A resourse of distributional similarity rules calculated with Idan's dist.sim. code using Lin's measure (without clustering) over the Reuters RCV1 corpus with dependency-based features.

POS: nouns

Ref to relevant Paper: “Automatic Retrieval and Clustering of Similar Words”, Dekang Lin, COLING-ACL, 1998, pp. 768-774.

DB Scheme: distsim (qa-srv:3308)

DB tables: lin_rules_lemmas

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Resource name: DIRECT-200 / DIRECT-1000

Implementation: Direct200LexicalResource / Direct1000LexicalResource

Resource description: Directional similarity rules calculated using the balancedAP (bap) measure over Reuters RCV1 corpus with dependency-based features. Downloabable from our homepage (http://u.cs.biu.ac.il/~nlp/downloads/DIRECT.html)

Direct1000LexicalResource - up to 1000 similarity rules per right-hand-side term (nouns and verbs)

Direct200LexicalResource - a part from the above, limited to up to 200 rules per term

POS: nouns & verbs

Ref to relevant Paper:

(1) Lili Kotlerman, Ido Dagan, Idan Szpektor and Maayan Zhitomirsky-Geffet. Directional Distributional Similarity for Lexical Inference. Special Issue of Natural Language Engineering on Distributional Lexical Semantics (JNLE-DLS), 2010.

(2) Lili Kotlerman, Ido Dagan, Idan Szpektor and Maayan Zhitomirsky-Geffet. Directional Distributional Similarity for Lexical Expansion. In Proceedings of ACL (short papers), 2009.

DB Scheme: bap (qa-srv:3308)

DB tables: direct_nouns_200, direct_verbs_200 / direct_nouns_1000, direct_verbs_1000

Manual ontologies

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Resource name: WordNet

Implementation: WordnetLexicalResource

Resource description: Uses WordNet relations which correspond to lexical entailment.

Ref to relevant Paper: Fellbaum, Christiane, ed. 1998. WordNet An Electronic Lexical Database. The MIT Press.

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Resource name: Wiktionary

Implementation: WiktionaryLexicalResource

Resource description: Uses Wikitionary relations to retrieve lexical entailment. See http://en.wiktionary.org/wiki/Wiktionary:Main_Page

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Resource name: Wikipedia

Implementation: WikiLexicalResourcee

Resource description: Lexical rules that were extracted automatically from English Wikipedia

Ref to relevant Paper: Eyal Shnarch, Libby Barak, Ido Dagan. Extracting Lexical Reference Rules from Wikipedia. ACL, 2009.

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Resource name: VerbOcean

Implementation: VerbOceanLexicalResource

Resource description: Extract lexical entailment rules from VerbOcean.

Ref to relevant Paper: Timothy Chklovski and Patrick Pantel. 2004.VerbOcean: Mining the Web for Fine-Grained Semantic Verb Relations. In Proceedings of Conference on Empirical Methods in Natural Language Processing (EMNLP-04). Barcelona, Spain.

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Resource name: Catvar

Implementation: CatvarLexicalResource

Resource description: Extract lexical entailment rules from CatVar

Ref to relevant Paper: Habash, Nizar and Bonnie Dorr, A Categorial Variation Database for English, Proceedings of the North American Association for Computational Linguistics, Edmonton, Canada, pp. 96--102, 2003