Difference between revisions of "RTE Knowledge Resources"

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| [[WordNet]]
 
| [[WordNet]]
 
| Lexical DB
 
| Lexical DB
| Princeton University
+
| George A. Miller (project director) - <br>Princeton University
 
| 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
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| [http://verbs.colorado.edu/~mpalmer/projects/verbnet.html Verbnet]
 
| [http://verbs.colorado.edu/~mpalmer/projects/verbnet.html Verbnet]
 
| Lexical DB
 
| Lexical DB
| University of Colorado Boulder
+
| Martha Palmer, Karin Kipper - <br>University of Colorado Boulder
 
| Lexicon for English verbs organized into classes
 
| Lexicon for English verbs organized into classes
 
| style="text-align: center;"|3
 
| style="text-align: center;"|3
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| [[VerbOcean]]
 
| [[VerbOcean]]
 
| Lexical DB
 
| Lexical DB
| University of Southern California
+
| Timothy Chklovski and Patrick Pantel - <br>Information Sciences Institute, University of Southern California
 
| Broad-coverage semantic network of verbs
 
| Broad-coverage semantic network of verbs
 
| style="text-align: center;"|5
 
| style="text-align: center;"|5
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| [http://framenet.icsi.berkeley.edu/ FrameNet]
 
| [http://framenet.icsi.berkeley.edu/ FrameNet]
 
| Lexical DB
 
| Lexical DB
| ICSI (International Computer Science Institute) - Berkley University
+
| Charles J. Fillmore (project director) - <br>ICSI (International Computer Science Institute) - Berkley University
 
| 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
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| [http://nlp.cs.nyu.edu/meyers/NomBank.html NomBank]
 
| [http://nlp.cs.nyu.edu/meyers/NomBank.html NomBank]
 
| Lexical DB
 
| Lexical DB
| New York University
+
| Adam Meyers, Ruth Reeves, Catherine Macleod, Rachel Szekely, Veronika Zielinska, Brian Young - <br>New York University
 
| 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
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| [http://verbs.colorado.edu/~mpalmer/projects/ace.html PropBank]
 
| [http://verbs.colorado.edu/~mpalmer/projects/ace.html PropBank]
 
| Lexical DB
 
| Lexical DB
| University of Colorado Boulder  
+
| Martha Palmer, Mitch Marcus - <br>University of Colorado Boulder  
 
| 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
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| [http://nlp.cs.nyu.edu/nomlex/index.html Nomlex] Plus
 
| [http://nlp.cs.nyu.edu/nomlex/index.html Nomlex] Plus
 
| Lexical DB
 
| Lexical DB
| New York University
+
| Catherine Macleod, Ralph Grishman, Adam Meyers, Leslie Barrett and Ruth Reeves - <br>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
 
| 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
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| [[TEASE]] Collection
 
| [[TEASE]] Collection
 
| Collection of Entailment Rules
 
| Collection of Entailment Rules
| Bar Ilan University
+
| Idan Szpektor - <br>Bar Ilan University
 
| Output of the TEASE algorithm  
 
| Output of the TEASE algorithm  
 
| style="text-align: center;"|0
 
| style="text-align: center;"|0
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| [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]
 
| Word List
 
| Word List
| BADC British Atmospheric Data Centre
+
| BADC (British Atmospheric Data Centre)
 
| Acronym and Abbreviation List
 
| Acronym and Abbreviation List
 
| style="text-align: center;"|1
 
| style="text-align: center;"|1
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| [http://www.cs.ualberta.ca/~lindek/downloads.htm Dekang Lin’s Thesaurus]
 
| [http://www.cs.ualberta.ca/~lindek/downloads.htm Dekang Lin’s Thesaurus]
 
| Thesaurus
 
| Thesaurus
| University of Alberta
+
| Dekang Lin - <br>University of Alberta
 
| 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
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| [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]
 
| Word list
 
| Word list
| Google Inc.
+
| Thorsten Brants, Alex Franz -  <br>Linguistic Data Consortium, University of Pennsylvania; 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
 
| 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
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| [http://geonames.usgs.gov/index.html GNIS - Geographic Names Information System]
 
| [http://geonames.usgs.gov/index.html GNIS - Geographic Names Information System]
 
| Gazetteer
 
| Gazetteer
| USGS - United States Geological Survey
+
| USGS (United States Geological Survey)
 
| 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
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| [http://nlp.cs.nyu.edu/paraphrase/ Sekine's Paraphrase Database]
 
| [http://nlp.cs.nyu.edu/paraphrase/ Sekine's Paraphrase Database]
 
| Collection of paraphrases
 
| Collection of paraphrases
| Department of Computer Science, New York University  
+
| Satoshi Sekine - <br>Department of Computer Science, New York University  
 
| Data-base created using Sekine's method, NOT cleaned up by human. It includes 19,975 sets of paraphrases with 191,572 phrases.
 
| Data-base created using Sekine's method, NOT cleaned up by human. It includes 19,975 sets of paraphrases with 191,572 phrases.
 
| style="text-align: center;"| 0
 
| style="text-align: center;"| 0
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| [http://www.cs.cornell.edu/~cristian/Without_a_doubt_-_Data.html Downward entailing operators]  
 
| [http://www.cs.cornell.edu/~cristian/Without_a_doubt_-_Data.html Downward entailing operators]  
 
| Collection of entailing operators
 
| Collection of entailing operators
| Department of Computer Science, Cornell University, Ithaca NY
+
| Cristian Danescu-Niculescu-Mizil - <br>Department of Computer Science, Cornell University, Ithaca NY
 
| System output of an unsupervised algorithm recovering many Downward Entailing operators, like 'doubt'.
 
| System output of an unsupervised algorithm recovering many Downward Entailing operators, like 'doubt'.
 
| style="text-align: center;"| 0
 
| style="text-align: center;"| 0

Revision as of 09:15, 19 June 2009

Knowledge resources have shown their relevance for applied semantic inference, and are extensively used by applied inference systems, such as those developed within the Textual Entailment framework.

This page presents a list of the knowledge resources used by systems that have participated in the last RTE challenges. The first table lists the publicly available resources, the second one lists unpublished resources. Both tables are sortable by Resource name, type, author and number of users.

RTE Participants are encouraged to add information about all kind of knowledge resources used, from standard existing resources (e.g. WordNet) to knowledge collections created for specific purposes, which can be made available to the community.


Publicly available Resources

Resource Type Author Brief description RTE Users* Usage info
WordNet Lexical DB George A. Miller (project director) -
Princeton University
Lexical database of English nouns, verbs, adjectives and adverbs 23 Users
Verbnet Lexical DB Martha Palmer, Karin Kipper -
University of Colorado Boulder
Lexicon for English verbs organized into classes 3 Users
VerbOcean Lexical DB Timothy Chklovski and Patrick Pantel -
Information Sciences Institute, University of Southern California
Broad-coverage semantic network of verbs 5 Users
FrameNet Lexical DB Charles J. Fillmore (project director) -
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 Adam Meyers, Ruth Reeves, Catherine Macleod, Rachel Szekely, Veronika Zielinska, Brian Young -
New York University
Lexical resource containing syntactic frames for nouns, extracted from annotated corpora 2 Users
PropBank Lexical DB Martha Palmer, Mitch Marcus -
University of Colorado Boulder
Lexical resource containing syntactic frames for verbs, extracted from annotated corpora 2 Users
Nomlex Plus Lexical DB Catherine Macleod, Ralph Grishman, Adam Meyers, Leslie Barrett and Ruth Reeves -
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
Wikipedia Encyclopedia Free encyclopedia. Used for extraction of lexical-semantic rules (from its more structured parts), named entity recognition, geographical information etc. 3 Users
TEASE Collection Collection of Entailment Rules Idan Szpektor -
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 Dekang Lin -
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 Thorsten Brants, Alex Franz -
Linguistic Data Consortium, University of Pennsylvania; 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
Sekine's Paraphrase Database Collection of paraphrases Satoshi Sekine -
Department of Computer Science, New York University
Data-base created using Sekine's method, NOT cleaned up by human. It includes 19,975 sets of paraphrases with 191,572 phrases. 0 Users
Microsoft Research Paraphrase Corpus Collection of paraphrases Microsoft Research Text file containing 5800 pairs of sentences which have been extracted from news sources on the web, along with human annotations indicating whether each pair captures a paraphrase/semantic equivalence relationship. 0 Users
Downward entailing operators Collection of entailing operators Cristian Danescu-Niculescu-Mizil -
Department of Computer Science, Cornell University, Ithaca NY
System output of an unsupervised algorithm recovering many Downward Entailing operators, like 'doubt'. 0 Users
New resource Participants are encouraged to contribute Users
New resource Participants are encouraged to contribute Users



Not available Resources

The following table lists the unpublished resources used by RTE participants. Some of them have been developed by Users themselves specifically for RTE. Interested people may turn to authors or users to obtain further information.

Resource Type Author Brief description RTE Users* Usage info
PARC Polarity Lexicon Lexical DB PARC - Palo Alto Research Center Verbs classification with respect to semantic polarity 1 Users
DIRT Paraphrase Collection Collection of paraphrases University of Alberta Output of the DIRT algorithm 4 Users
Gazetteer from TREC Gazetteer NIST - National Institute of Standards and Technology Cities and other geographical names 1 Users
DFKI Geographic Ontology
(to be released)
Ontology DFKI - German Research Center for Artificial Intelligence Ontology containing geographic terms and two kinds of relations: the directional part-of relation, and the equal relation for synonyms and abbreviations of the same geographic area (e.g the United Kingdom, the UK, Great Britain, etc.) 1 Users
Syntactic rule base
(to be released)
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
(to be released)
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. Extends a resource described in (Bar-Haim et al., AAAI-07) 1 Users
Lexical-Syntactic rule base combining WordNet, NomLex-plus and Unary DIRT Collection of Entailment Rules Bar-Ilan University Extract lexical-syntactic entailment rules for predicates (verbal and nominal), including argument mapping. The resource is based on WordNet, Nomlex-Plus and Unary DIRT (Szpektor and Dagan, Coling 08) 1 Users
Lexical reference rules extracted from Wikipedia
(to be released)
Collection of Entailment Rules Bar-Ilan University Extraction of lexical entailment rules from the text body (first sentence), and from metadata (links, redirects, parentheses) 1 Users
OPENU Collection Collection of Entailment Rules and Patterns Open University 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 number of Users (see "Usage Info" links for details) refers to participants in the last two RTE challenges.
RTE-3 data have been provided only by participants, whereas RTE-4 data have been integrated with information extracted from the related proceedings.