Detailed Information on Publication Record
2012
Common Sense Inference using Verb Valency Frames
NEVĚŘILOVÁ, Zuzana and Marek GRÁCBasic information
Original name
Common Sense Inference using Verb Valency Frames
Authors
NEVĚŘILOVÁ, Zuzana (203 Czech Republic, guarantor, belonging to the institution) and Marek GRÁC (703 Slovakia, belonging to the institution)
Edition
Berlin / Heidelberg, Proceedings of 15th International Conference on Text, Speech and Dialogue, p. 328-335, 8 pp. 2012
Publisher
Springer
Other information
Language
English
Type of outcome
Stať ve sborníku
Field of Study
10201 Computer sciences, information science, bioinformatics
Country of publisher
Czech Republic
Confidentiality degree
není předmětem státního či obchodního tajemství
Publication form
printed version "print"
Impact factor
Impact factor: 0.402 in 2005
RIV identification code
RIV/00216224:14330/12:00057557
Organization unit
Faculty of Informatics
ISBN
978-3-642-32789-6
ISSN
UT WoS
000337298700040
Keywords in English
common sense inference; common sense; implicit knowledge; verb valency; valency frame; valency lexicon
Tags
Tags
International impact, Reviewed
Změněno: 6/4/2015 22:19, Mgr. Vendula Hromádková
Abstract
V originále
In this paper we discuss common-sense reasoning from verb valency frames. While seeing verbs as predicates is not a new approach, processing inference as a transformation of valency frames is a promising method we developed with the help of large verb valency lexicons. We went through the whole process and evaluated it on several levels: parsing, valency assignment, syntactic transformation, syntactic and semantic evaluation of the generated propositions. We have chosen the domain of cooking recipes. We built a corpus with marked noun phrases, verb phrases and dependencies among them. We have manually created a basic set of inference rules and used it to infer new propositions from the corpus. Next, we extended this basic set and repeated the process. At first, we generated 1,738 sentences from 175 rules. 1,633 sentences were judged as (syntactically) correct and 1,533 were judged as (semantically) true. After extending the basic rule set we generated 2,826 propositions using 276 rules. 2,598 propositions were judged correct and 2,433 of the propositions were judged true.
Links
GAP401/10/0792, research and development project |
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LM2010013, research and development project |
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