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Common Sense Inference using Verb Valency Frames

česky | in English

NEVĚŘILOVÁ, Zuzana and Marek GRÁC. Common Sense Inference using Verb Valency Frames. In Sojka, Petr and Horák, Aleš and Kopeček, Ivan and Pala, Karel. Proceedings of 15th International Conference on Text, Speech and Dialogue. Berlin / Heidelberg: Springer, 2012. p. 328-335, 8 pp. ISBN 978-3-642-32789-6. doi:10.1007/978-3-642-32790-2_40.
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Basic 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
Original language English
Type of outcome Stať ve sborníku
Field of Study Computer sciences, information science, bioinformatics
Country of publisher Czech Republic
Confidentiality degree is not subject to a state or trade secret
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 0302-9743
Doi http://dx.doi.org/10.1007/978-3-642-32790-2_40
UT WoS 000337298700040
Keywords in English common sense inference; common sense; implicit knowledge; verb valency; valency frame; valency lexicon
Tags best1
Tags International impact, Reviewed
Changed by Changed by: Mgr. Vendula Hromádková, učo 108933. Changed: 6. 4. 2015 22:19.
Abstract
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 projectName: Temporální aspekty znalostí a informací
Investor: Czech Science Foundation, Standard Projects
LM2010013, research and development projectName: LINDAT-CLARIN: Institut pro analýzu, zpracování a distribuci lingvistických dat (Acronym: LINDAT-Clarin)
Investor: Ministry of Education, Youth and Sports of the CR, Large Infrastructures for Research, Development and Innovation
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