RTE Knowledge Resources

The table below lists the knowledge resources used by participants in the last RTE challenges.

Resource	Type	Author	Brief description	# Users*	Usage info
WordNet	Lexical	Princeton University	Lexical database of English nouns, verbs, adjectives and adverbs	23	Users
Verbnet	Lexical	University of Colorado Boulder	On-line lexicon for English verbs organized into classes	3	Users
VerbOcean	Lexical	University of Southern California	Broad-coverage semantic network of verbs	5	Users
FrameNet	Lexical	Berkeley FrameNet project	On-line lexical resource for English words, based on frame semantics (valences) and supported by corpus evidence	2	Users
NomBank Resources	Lexical	New York University	Lexical Resources containing syntactic frames for nouns, extracted from annotated corpora	2	Users
Nomlex Plus	Lexical	Proteus Project - 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	PARC - Palo Alto Research Center	Verbs classification with respect to semantic polarity	1	Users
DIRT Paraphrase Collection	Collections of paraphrases (DIRT output)	Various	Output of the DIRT algorithm	4	Users
PropBank Resources	Lexical	University of Colorado Boulder	Lexical Resources containing syntactic frames for verbs, extracted from annotated corpora	2	Users
TEASE Collection	Syntactic-semantic	Bar Ilan University	Collection of Entailment Rules	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
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
Wikipedia	Encyclopedia				Users
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[*] Details about Users in the related links in the "Usage info" column.