Difference between revisions of "RTE Knowledge Resources"

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| Lexical database of English nouns, verbs, adjectives and adverbs
 
| Lexical database of English nouns, verbs, adjectives and adverbs
 
| style="text-align: center;"|23
 
| style="text-align: center;"|23
| [[WordNet RTE Users|Users]]
+
| [[WordNet - RTE Users|Users]]
 
|- bgcolor="#ECECEC" "align="left"
 
|- bgcolor="#ECECEC" "align="left"
 
| [http://verbs.colorado.edu/~mpalmer/projects/verbnet.html Verbnet]
 
| [http://verbs.colorado.edu/~mpalmer/projects/verbnet.html Verbnet]
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| Lexicon for English verbs organized into classes
 
| Lexicon for English verbs organized into classes
 
| style="text-align: center;"|3
 
| style="text-align: center;"|3
| [[Verbnet RTE Users|Users]]
+
| [[Verbnet - RTE Users|Users]]
 
|- bgcolor="#ECECEC" "align="left"
 
|- bgcolor="#ECECEC" "align="left"
 
| [[VerbOcean]]
 
| [[VerbOcean]]
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| Broad-coverage semantic network of verbs
 
| Broad-coverage semantic network of verbs
 
| style="text-align: center;"|5
 
| style="text-align: center;"|5
| [[VerbOcean RTE Users|Users]]
+
| [[VerbOcean - RTE Users|Users]]
 
|- bgcolor="#ECECEC" "align="left"
 
|- bgcolor="#ECECEC" "align="left"
 
| [http://framenet.icsi.berkeley.edu/ FrameNet]
 
| [http://framenet.icsi.berkeley.edu/ FrameNet]
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| Lexical resource for English words, based on frame semantics (valences) and supported by corpus evidence
 
| Lexical resource for English words, based on frame semantics (valences) and supported by corpus evidence
 
| style="text-align: center;"|2
 
| style="text-align: center;"|2
| [[Framenet RTE Users|Users]]
+
| [[Framenet - RTE Users|Users]]
 
|- bgcolor="#ECECEC" "align="left"
 
|- bgcolor="#ECECEC" "align="left"
 
| [http://nlp.cs.nyu.edu/meyers/NomBank.html NomBank]
 
| [http://nlp.cs.nyu.edu/meyers/NomBank.html NomBank]
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| Lexical resource containing syntactic frames for nouns, extracted from annotated corpora  
 
| Lexical resource containing syntactic frames for nouns, extracted from annotated corpora  
 
| style="text-align: center;"|2
 
| style="text-align: center;"|2
| [[NomBank Resources RTE Users|Users]]  
+
| [[NomBank Resource - RTE Users|Users]]  
 
|- bgcolor="#ECECEC" "align="left"
 
|- bgcolor="#ECECEC" "align="left"
 
| [http://verbs.colorado.edu/~mpalmer/projects/ace.html PropBank]
 
| [http://verbs.colorado.edu/~mpalmer/projects/ace.html PropBank]
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| Lexical resource containing syntactic frames for verbs, extracted from annotated corpora  
 
| Lexical resource containing syntactic frames for verbs, extracted from annotated corpora  
 
| style="text-align: center;"|2
 
| style="text-align: center;"|2
| [[PropBank Resources RTE Users|Users]]
+
| [[PropBank Resource - RTE Users|Users]]
 
|- bgcolor="#ECECEC" "align="left"
 
|- bgcolor="#ECECEC" "align="left"
 
| [http://nlp.cs.nyu.edu/nomlex/index.html Nomlex] Plus
 
| [http://nlp.cs.nyu.edu/nomlex/index.html Nomlex] Plus
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| Dictionary of English nominalizations: it describes the allowed complements for a nominalization and relates the nominal complements to the arguments of the corresponding verb
 
| Dictionary of English nominalizations: it describes the allowed complements for a nominalization and relates the nominal complements to the arguments of the corresponding verb
 
| style="text-align: center;"|1
 
| style="text-align: center;"|1
| [[Nomlex Plus RTE Users|Users]]
+
| [[Nomlex Plus - RTE Users|Users]]
 
|- bgcolor="#ECECEC" "align="left"
 
|- bgcolor="#ECECEC" "align="left"
 
| Parc Polarity Lexicon
 
| Parc Polarity Lexicon
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| Verbs classification with respect to semantic polarity
 
| Verbs classification with respect to semantic polarity
 
| style="text-align: center;"|1
 
| style="text-align: center;"|1
| [[Parc Polarity Lexicon RTE Users|Users]]
+
| [[Parc Polarity Lexicon - RTE Users|Users]]
 
|- bgcolor="#ECECEC" "align="left"
 
|- bgcolor="#ECECEC" "align="left"
 
| [http://www.wikipedia.org/ Wikipedia]
 
| [http://www.wikipedia.org/ Wikipedia]
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| Free encyclopedia. Used for extraction of lexical-semantic rules (from its more structured parts), named entity recognition, geographical information etc.
 
| Free encyclopedia. Used for extraction of lexical-semantic rules (from its more structured parts), named entity recognition, geographical information etc.
 
| style="text-align: center;"|3
 
| style="text-align: center;"|3
| [[Wikipedia RTE Users|Users]]
+
| [[Wikipedia - RTE Users|Users]]
 
|- bgcolor="#ECECEC" "align="left"
 
|- bgcolor="#ECECEC" "align="left"
 
| [[DIRT Paraphrase Collection]]
 
| [[DIRT Paraphrase Collection]]
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| Output of the DIRT algorithm  
 
| Output of the DIRT algorithm  
 
| style="text-align: center;"|4
 
| style="text-align: center;"|4
| [[DIRT Paraphrase Collections RTE Users|Users]]
+
| [[DIRT Paraphrase Collection - RTE Users|Users]]
 
|- bgcolor="#ECECEC" "align="left"
 
|- bgcolor="#ECECEC" "align="left"
 
| [[TEASE]] Collection
 
| [[TEASE]] Collection
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| Output of the TEASE algorithm  
 
| Output of the TEASE algorithm  
 
| style="text-align: center;"|0
 
| style="text-align: center;"|0
| [[Tease Collection RTE Users|Users]]
+
| [[Tease Collection - RTE Users|Users]]
 
|- bgcolor="#ECECEC" "align="left"
 
|- bgcolor="#ECECEC" "align="left"
 
| [http://badc.nerc.ac.uk/help/abbrevs.html BADC Acronym and Abbreviation List]
 
| [http://badc.nerc.ac.uk/help/abbrevs.html BADC Acronym and Abbreviation List]
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| Acronym and Abbreviation List
 
| Acronym and Abbreviation List
 
| style="text-align: center;"|1
 
| style="text-align: center;"|1
| [[BADC Acronym and Abbreviation List RTE Users|Users]]
+
| [[BADC Acronym and Abbreviation List - RTE Users|Users]]
 
|- bgcolor="#ECECEC" "align="left"
 
|- bgcolor="#ECECEC" "align="left"
 
| [http://www.acronym-guide.com/ Acronym Guide]
 
| [http://www.acronym-guide.com/ Acronym Guide]
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| Acronym and Abbreviation Lists for English, branched in thematic directories  
 
| Acronym and Abbreviation Lists for English, branched in thematic directories  
 
| style="text-align: center;"|1
 
| style="text-align: center;"|1
| [[Acronym Guide RTE Users|Users]]
+
| [[Acronym Guide - RTE Users|Users]]
 
|- bgcolor="#ECECEC" "align="left"
 
|- bgcolor="#ECECEC" "align="left"
 
| [http://www.cs.ualberta.ca/~lindek/downloads.htm Dekang Lin’s Thesaurus]
 
| [http://www.cs.ualberta.ca/~lindek/downloads.htm Dekang Lin’s Thesaurus]
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| Thesaurus automatically constructed using a parsed corpus, based on distributional similarity scores
 
| Thesaurus automatically constructed using a parsed corpus, based on distributional similarity scores
 
| style="text-align: center;"|1
 
| style="text-align: center;"|1
| [[Dekang Lin’s Thesaurus RTE Users|Users]]
+
| [[Dekang Lin’s Thesaurus - RTE Users|Users]]
 
|- bgcolor="#ECECEC" "align="left"
 
|- bgcolor="#ECECEC" "align="left"
 
| [http://en.wikipedia.org/wiki/Roget%27s_Thesaurus Roget's Thesaurus]
 
| [http://en.wikipedia.org/wiki/Roget%27s_Thesaurus Roget's Thesaurus]
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| Roget's Thesaurus is a widely-used English thesaurus, created by Dr. Peter Mark Roget in 1805. The original edition had 15,000 words, and each new edition has been larger. The electronic edition ([http://machaut.uchicago.edu/rogets version 1.02]) is made available by University of Chicago.
 
| Roget's Thesaurus is a widely-used English thesaurus, created by Dr. Peter Mark Roget in 1805. The original edition had 15,000 words, and each new edition has been larger. The electronic edition ([http://machaut.uchicago.edu/rogets version 1.02]) is made available by University of Chicago.
 
| style="text-align: center;"|1
 
| style="text-align: center;"|1
| [[Roget's Thesaurus RTE Users|Users]]
+
| [[Roget's Thesaurus - RTE Users|Users]]
 
|- bgcolor="#ECECEC" "align="left"
 
|- bgcolor="#ECECEC" "align="left"
 
| [http://www.ldc.upenn.edu/Catalog/CatalogEntry.jsp?catalogId=LDC2006T13 Web1T 5-grams]
 
| [http://www.ldc.upenn.edu/Catalog/CatalogEntry.jsp?catalogId=LDC2006T13 Web1T 5-grams]
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| Data set containing English word n-grams and their observed frequency counts. The n-gram counts were generated from approximately 1 trillion word tokens of text from publicly accessible Web pages
 
| Data set containing English word n-grams and their observed frequency counts. The n-gram counts were generated from approximately 1 trillion word tokens of text from publicly accessible Web pages
 
| style="text-align: center;"|1
 
| style="text-align: center;"|1
| [[Web1T RTE Users|Users]]
+
| [[Web1T - RTE Users|Users]]
 
|- bgcolor="#ECECEC" "align="left"
 
|- bgcolor="#ECECEC" "align="left"
 
| [http://geonames.usgs.gov/index.html GNIS - Geographic Names Information System]
 
| [http://geonames.usgs.gov/index.html GNIS - Geographic Names Information System]
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| Database containing the Federal and national standard toponyms for USA, associated areas and Antarctica
 
| Database containing the Federal and national standard toponyms for USA, associated areas and Antarctica
 
| style="text-align: center;"|1
 
| style="text-align: center;"|1
| [[GNIS RTE Users|Users]]
+
| [[GNIS - RTE Users|Users]]
 
|- bgcolor="#ECECEC" "align="left"
 
|- bgcolor="#ECECEC" "align="left"
 
| [http://www.geonames.org/ Geonames]
 
| [http://www.geonames.org/ Geonames]
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| Database containing eight million geographical names. It is integrating geographical data such as names of places in various languages, elevation, population and others from various sources.
 
| Database containing eight million geographical names. It is integrating geographical data such as names of places in various languages, elevation, population and others from various sources.
 
| style="text-align: center;"|1
 
| style="text-align: center;"|1
| [[Geonames RTE Users|Users]]
+
| [[Geonames - RTE Users|Users]]
 
|- bgcolor="#ECECEC" "align="left"
 
|- bgcolor="#ECECEC" "align="left"
 
| Gazetteer from [http://trec.nist.gov/ TREC]
 
| Gazetteer from [http://trec.nist.gov/ TREC]
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| Cities and other geographical names
 
| Cities and other geographical names
 
| style="text-align: center;"|1  
 
| style="text-align: center;"|1  
| [[Gazetteers from TREC RTE Users|Users]]
+
| [[Gazetteers from TREC - RTE Users|Users]]
 
|- bgcolor="#ECECEC" "align="left"
 
|- bgcolor="#ECECEC" "align="left"
 
| [http://vissim.uwf.edu/index.htm Geographic Ontology]
 
| [http://vissim.uwf.edu/index.htm Geographic Ontology]
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| Hierarchical data structure that allows the storage of natural and man-made feature data for use in a multitude of both manual and computerized Mapping, Charting & Geodesy systems  
 
| Hierarchical data structure that allows the storage of natural and man-made feature data for use in a multitude of both manual and computerized Mapping, Charting & Geodesy systems  
 
| style="text-align: center;"|1
 
| style="text-align: center;"|1
| [[Geographic Ontology RTE Users|Users]]
+
| [[Geographic Ontology - RTE Users|Users]]
 
|- bgcolor="#ECECEC" "align="left"
 
|- bgcolor="#ECECEC" "align="left"
 
| Syntactic rule base
 
| Syntactic rule base
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| A manually-composed collection of entailment rules which define parse tree transformations. The rules cover generic syntactic phenomena such as appositions, conjunctions, passive, relative clause,  etc. (Bar-Haim et al., AAAI-07)  
 
| A manually-composed collection of entailment rules which define parse tree transformations. The rules cover generic syntactic phenomena such as appositions, conjunctions, passive, relative clause,  etc. (Bar-Haim et al., AAAI-07)  
 
| style="text-align: center;"|1
 
| style="text-align: center;"|1
| [[Syntactic rule base RTE Users|Users]]
+
| [[Syntactic rule base - RTE Users|Users]]
 
|- bgcolor="#ECECEC" "align="left"
 
|- bgcolor="#ECECEC" "align="left"
 
| Polarity rule base
 
| Polarity rule base
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| A manually-composed collection of entailment rules which detect predicates whose polarity is negative (e.g. didn't dance) or unknown (e.g. plans to dance). The rules capture diverse phenomena that affect polarity, e.g. verbal negation, modal verbs, conditionals, and certain verbs that induce negative or "unknown" polarity context. The latter were taken mainly from VerbNet, and also from the PARC polarity lexicon. It extends a resource described in (Bar-Haim et al., AAAI-07)  
 
| A manually-composed collection of entailment rules which detect predicates whose polarity is negative (e.g. didn't dance) or unknown (e.g. plans to dance). The rules capture diverse phenomena that affect polarity, e.g. verbal negation, modal verbs, conditionals, and certain verbs that induce negative or "unknown" polarity context. The latter were taken mainly from VerbNet, and also from the PARC polarity lexicon. It extends a resource described in (Bar-Haim et al., AAAI-07)  
 
| style="text-align: center;"|1  
 
| style="text-align: center;"|1  
| [[Polarity rule base RTE Users|Users]]
+
| [[Polarity rule base - RTE Users|Users]]
 
|- bgcolor="#ECECEC" "align="left"
 
|- bgcolor="#ECECEC" "align="left"
 
| OPENU Collection
 
| OPENU Collection
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| Collections of rules, patterns etc. for RTE purpose, extracted from parsed Reuter corpus.
 
| Collections of rules, patterns etc. for RTE purpose, extracted from parsed Reuter corpus.
 
| style="text-align: center;"|1
 
| style="text-align: center;"|1
| [[Collections extracted from Parsed Corpora RTE Users|Users]]
+
| [[OPENU Collection - RTE Users|Users]]
 
|- bgcolor="#ECECEC" "align="left"
 
|- bgcolor="#ECECEC" "align="left"
 
| ''New resource''
 
| ''New resource''
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| ''Participants are encouraged to contribute''
 
| ''Participants are encouraged to contribute''
 
| style="text-align: center;"|  
 
| style="text-align: center;"|  
| [[New Resource1 RTE Users|Users]]
+
| [[New Resource1 - RTE Users|Users]]
 
|- bgcolor="#ECECEC" "align="left"
 
|- bgcolor="#ECECEC" "align="left"
 
| ''New resource''
 
| ''New resource''
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| ''Participants are encouraged to contribute''
 
| ''Participants are encouraged to contribute''
 
| style="text-align: center;"|  
 
| style="text-align: center;"|  
| [[New Resource2 RTE Users|Users]]
+
| [[New Resource2 - RTE Users|Users]]
 
|}
 
|}
 
<br>
 
<br>
 
[*] The numbers refer to the Users in RTE4 (data extracted both from related proceedings and from RTE Knowledge Resources Questionnaire) and in RTE3 (data extracted only from RTE Knowledge Resources Questionnaire) challenges.
 
[*] The numbers refer to the Users in RTE4 (data extracted both from related proceedings and from RTE Knowledge Resources Questionnaire) and in RTE3 (data extracted only from RTE Knowledge Resources Questionnaire) challenges.

Revision as of 04:01, 21 April 2009

The table below lists the knowledge resources used by participants in the last RTE challenges. Other important RTE resources have been added in order to encourage people to add information about potential usage.
The table is sortable by Resource name, type, author and number of users.

Resource Type Author Brief description RTE Users* Usage info
WordNet Lexical DB Princeton University Lexical database of English nouns, verbs, adjectives and adverbs 23 Users
Verbnet Lexical DB University of Colorado Boulder Lexicon for English verbs organized into classes 3 Users
VerbOcean Lexical DB University of Southern California Broad-coverage semantic network of verbs 5 Users
FrameNet Lexical DB ICSI (International Computer Science Institute) - Berkley University Lexical resource for English words, based on frame semantics (valences) and supported by corpus evidence 2 Users
NomBank Lexical DB New York University Lexical resource containing syntactic frames for nouns, extracted from annotated corpora 2 Users
PropBank Lexical DB University of Colorado Boulder Lexical resource containing syntactic frames for verbs, extracted from annotated corpora 2 Users
Nomlex Plus Lexical DB New York University Dictionary of English nominalizations: it describes the allowed complements for a nominalization and relates the nominal complements to the arguments of the corresponding verb 1 Users
Parc Polarity Lexicon Lexical DB PARC - Palo Alto Research Center Verbs classification with respect to semantic polarity 1 Users
Wikipedia Encyclopedia Free encyclopedia. Used for extraction of lexical-semantic rules (from its more structured parts), named entity recognition, geographical information etc. 3 Users
DIRT Paraphrase Collection Collection of paraphrases University of Alberta Output of the DIRT algorithm 4 Users
TEASE Collection Collection of Entailment Rules Bar Ilan University Output of the TEASE algorithm 0 Users
BADC Acronym and Abbreviation List Word List BADC - British Atmospheric Data Centre Acronym and Abbreviation List 1 Users
Acronym Guide Word List Acronym-Guide.com Acronym and Abbreviation Lists for English, branched in thematic directories 1 Users
Dekang Lin’s Thesaurus Thesaurus University of Alberta Thesaurus automatically constructed using a parsed corpus, based on distributional similarity scores 1 Users
Roget's Thesaurus Thesaurus Peter Mark Roget (Electronic version distributed by University of Chicago) Roget's Thesaurus is a widely-used English thesaurus, created by Dr. Peter Mark Roget in 1805. The original edition had 15,000 words, and each new edition has been larger. The electronic edition (version 1.02) is made available by University of Chicago. 1 Users
Web1T 5-grams Word list Google Inc. Data set containing English word n-grams and their observed frequency counts. The n-gram counts were generated from approximately 1 trillion word tokens of text from publicly accessible Web pages 1 Users
GNIS - Geographic Names Information System Gazetteer USGS - United States Geological Survey Database containing the Federal and national standard toponyms for USA, associated areas and Antarctica 1 Users
Geonames Gazetteer Database containing eight million geographical names. It is integrating geographical data such as names of places in various languages, elevation, population and others from various sources. 1 Users
Gazetteer from TREC Gazetteer NIST - National Institute of Standards and Technology Cities and other geographical names 1 Users
Geographic Ontology Ontology University of West Florida Hierarchical data structure that allows the storage of natural and man-made feature data for use in a multitude of both manual and computerized Mapping, Charting & Geodesy systems 1 Users
Syntactic rule base Collection of Entailment Rules Bar-Ilan University A manually-composed collection of entailment rules which define parse tree transformations. The rules cover generic syntactic phenomena such as appositions, conjunctions, passive, relative clause, etc. (Bar-Haim et al., AAAI-07) 1 Users
Polarity rule base Collection of Entailment Rules Bar-Ilan University A manually-composed collection of entailment rules which detect predicates whose polarity is negative (e.g. didn't dance) or unknown (e.g. plans to dance). The rules capture diverse phenomena that affect polarity, e.g. verbal negation, modal verbs, conditionals, and certain verbs that induce negative or "unknown" polarity context. The latter were taken mainly from VerbNet, and also from the PARC polarity lexicon. It extends a resource described in (Bar-Haim et al., AAAI-07) 1 Users
OPENU Collection Collection of Rules Collections of rules, patterns etc. for RTE purpose, extracted from parsed Reuter corpus. 1 Users
New resource Participants are encouraged to contribute Users
New resource Participants are encouraged to contribute Users


[*] The numbers refer to the Users in RTE4 (data extracted both from related proceedings and from RTE Knowledge Resources Questionnaire) and in RTE3 (data extracted only from RTE Knowledge Resources Questionnaire) challenges.