Acquiring Data for Textual Entailment Recognition

D 2013

Acquiring Data for Textual Entailment Recognition

NEVĚŘILOVÁ, Zuzana

Základní údaje

Originální název

Acquiring Data for Textual Entailment Recognition

Autoři

NEVĚŘILOVÁ, Zuzana (203 Česká republika, garant, domácí)

Vydání

Brno, Seventh Workshop on Recent Advances in Slavonic Natural Language Processing, RASLAN 2013, od s. 29-37, 9 s. 2013

Nakladatel

Tribun EU

Další údaje

Jazyk

angličtina

Typ výsledku

Stať ve sborníku

Obor

10201 Computer sciences, information science, bioinformatics

Stát vydavatele

Česká republika

Utajení

není předmětem státního či obchodního tajemství

Forma vydání

tištěná verze "print"

Odkazy

URL

Kód RIV

RIV/00216224:14330/13:00070350

Organizační jednotka

Fakulta informatiky

ISBN

978-80-263-0520-0

EID Scopus

2-s2.0-84897931679

Klíčová slova anglicky

extual entailment; language game; games with a purpose; GWAP;

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 27. 5. 2021 09:12, RNDr. Zuzana Nevěřilová, Ph.D.

Anotace

V originále

Language resources are hardly ever large enough. Building language resources that can be used as a gold standard for semantic analysis requires effort and investment. We present a prototype for acquiring language resources by means of a language game which is a cheap but long-term method. Games employed to acquire language resources are not new. For example games with a purpose are used for collecting common sense knowledge. The game presented in this paper is a work in progress. It collects annotated pairs text–hypothesis suitable for recognizing textual entailment in Czech. The game narrative is based on Sherlock Holmes and dr. Watson dialogues. For generating the dialogue line we use rule-based approaches such as syntactic analysis, anaphora resolution, synonym and hypernym replacement, word order rearrangement and verb frame based inference. To generate natural sounding sentences we added a language model score (based on n-gram frequencies in a corpus).

Návaznosti

LM2010013, projekt VaV

Název: LINDAT-CLARIN: Institut pro analýzu, zpracování a distribuci lingvistických dat (Akronym: LINDAT-Clarin)

Investor: Ministerstvo školství, mládeže a tělovýchovy ČR, Projekt LINDAT-Clarin - Vybudování a provoz českého uzlu pan-evropské infrastruktury pro výzkum

Citovat

NEVĚŘILOVÁ, Zuzana. Acquiring Data for Textual Entailment Recognition. In Seventh Workshop on Recent Advances in Slavonic Natural Language Processing, RASLAN 2013. Brno: Tribun EU, 2013, s. 29-37. ISBN 978-80-263-0520-0.

@inproceedings{1131901,
   author = {Nevěřilová, Zuzana},
   address = {Brno},
   booktitle = {Seventh Workshop on Recent Advances in Slavonic Natural Language Processing, RASLAN 2013},
   keywords = {extual entailment; language game; games with a purpose; GWAP;},
   howpublished = {tištěná verze "print"},
   language = {eng},
   location = {Brno},
   isbn = {978-80-263-0520-0},
   pages = {29-37},
   publisher = {Tribun EU},
   title = {Acquiring Data for Textual Entailment Recognition},
   url = {https://nlp.fi.muni.cz/raslan/2013/paper02.pdf},
   year = {2013}
}

TY  - CONF
ID  - 1131901
AU  - Nevěřilová, Zuzana
PY  - 2013
TI  - Acquiring Data for Textual Entailment Recognition
PB  - Tribun EU
CY  - Brno
SN  - 9788026305200
KW  - extual entailment
KW  - language game
KW  - games with a purpose
KW  - GWAP;
UR  - https://nlp.fi.muni.cz/raslan/2013/paper02.pdf
N2  - Language resources are hardly ever large enough. Building language resources that can be used as a gold standard for semantic analysis requires effort and investment. We present a prototype for acquiring language resources by means of a language game which is a cheap but long-term method. Games employed to acquire language resources are not new. For example games with a purpose are used for collecting common sense knowledge. The game presented in this paper is a work in progress. It collects annotated pairs text–hypothesis suitable for recognizing textual entailment in Czech. The game narrative is based on Sherlock Holmes and dr. Watson dialogues. For generating the dialogue line we use rule-based approaches such as syntactic analysis, anaphora resolution, synonym and hypernym replacement, word order rearrangement and verb frame based inference. To generate natural sounding sentences we added a language model score (based on n-gram frequencies in a corpus).
ER  -

NEVĚŘILOVÁ, Zuzana. Acquiring Data for Textual Entailment Recognition. In \textit{Seventh Workshop on Recent Advances in Slavonic Natural Language Processing, RASLAN 2013}. Brno: Tribun EU, 2013, s.~29-37. ISBN~978-80-263-0520-0.

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