Finding Definitions in Large Corpora with Sketch Engine

D 2016

Finding Definitions in Large Corpora with Sketch Engine

KOVÁŘ, Vojtěch, Monika MOČIARIKOVÁ a Pavel RYCHLÝ

Základní údaje

Originální název

Finding Definitions in Large Corpora with Sketch Engine

Autoři

KOVÁŘ, Vojtěch (203 Česká republika, garant, domácí), Monika MOČIARIKOVÁ (703 Slovensko, domácí) a Pavel RYCHLÝ (203 Česká republika, domácí)

Vydání

Portorož, Slovenia, Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016), od s. 391-394, 4 s. 2016

Nakladatel

European Language Resources Association (ELRA)

Další údaje

Jazyk

angličtina

Typ výsledku

Stať ve sborníku

Obor

10201 Computer sciences, information science, bioinformatics

Stát vydavatele

Francie

Utajení

není předmětem státního či obchodního tajemství

Forma vydání

paměťový nosič (CD, DVD, flash disk)

Kód RIV

RIV/00216224:14330/16:00088334

Organizační jednotka

Fakulta informatiky

ISBN

978-2-9517408-9-1

Klíčová slova anglicky

Sketch Engine; definition; definitions; CQL; corpora

Štítky

firank_B

Změněno: 20. 12. 2016 13:55, doc. Mgr. Pavel Rychlý, Ph.D.

Anotace

V originále

The paper describes automatic definition finding implemented within the leading corpus query and management tool, Sketch Engine. The implementation exploits complex pattern-matching queries in the corpus query language (CQL) and the indexing mechanism of word sketches for finding and storing definition candidates throughout the corpus. The approach is evaluated for Czech and English corpora, showing that the results are usable in practice: precision of the tool ranges between 30 and 75 percent (depending on the major corpus text types) and we were able to extract nearly 2 million definition candidates from an English corpus with 1.4 billion words. The feature is embedded into the interface as a concordance filter, so that users can search for definitions of any query to the corpus, including very specific multi-word queries. The results also indicate that ordinary texts (unlike explanatory texts) contain rather low number of definitions, which is perhaps the most important problem with automatic definition finding in general.

Návaznosti

GA15-13277S, projekt VaV

Název: Hyperintensionální logika pro analýzu přirozeného jazyka

Investor: Grantová agentura ČR, Hyperintensionální logika pro analýzu přirozeného jazyka

7F14047, projekt VaV

Název: Harvesting big text data for under-resourced languages (Akronym: HaBiT)

Investor: Ministerstvo školství, mládeže a tělovýchovy ČR, Harvesting big text data for under-resourced languages

Citovat

KOVÁŘ, Vojtěch, Monika MOČIARIKOVÁ a Pavel RYCHLÝ. Finding Definitions in Large Corpora with Sketch Engine. In Nicoletta Calzolari (Conference Chair) et al. Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016). Portorož, Slovenia: European Language Resources Association (ELRA), 2016, s. 391-394. ISBN 978-2-9517408-9-1.

@inproceedings{1360550,
   author = {Kovář, Vojtěch and Močiariková, Monika and Rychlý, Pavel},
   address = {Portorož, Slovenia},
   booktitle = {Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016)},
   editor = {Nicoletta Calzolari (Conference Chair) et al.},
   keywords = {Sketch Engine; definition; definitions; CQL; corpora},
   howpublished = {paměťový nosič},
   language = {eng},
   location = {Portorož, Slovenia},
   isbn = {978-2-9517408-9-1},
   pages = {391-394},
   publisher = {European Language Resources Association (ELRA)},
   title = {Finding Definitions in Large Corpora with Sketch Engine},
   year = {2016}
}

TY  - JOUR
ID  - 1360550
AU  - Kovář, Vojtěch - Močiariková, Monika - Rychlý, Pavel
PY  - 2016
TI  - Finding Definitions in Large Corpora with Sketch Engine
PB  - European Language Resources Association (ELRA)
CY  - Portorož, Slovenia
SN  - 9782951740891
KW  - Sketch Engine
KW  - definition
KW  - definitions
KW  - CQL
KW  - corpora
N2  - The paper describes automatic definition finding implemented within the leading corpus query and management tool, Sketch Engine. The implementation exploits complex pattern-matching queries in the corpus query language (CQL) and the indexing mechanism of word sketches for finding and storing definition candidates throughout the corpus. The approach is evaluated for Czech and English corpora, showing that the results are usable in practice: precision of the tool ranges between 30 and 75 percent (depending on the major corpus text types) and we were able to extract nearly 2 million definition candidates from an English corpus with 1.4 billion words. The feature is embedded into the interface as a concordance filter, so that users can search for definitions of any query to the corpus, including very specific multi-word queries. The results also indicate that ordinary texts (unlike explanatory texts) contain rather low number of definitions, which is perhaps the most important problem with automatic definition finding in general.
ER  -

KOVÁŘ, Vojtěch, Monika MOČIARIKOVÁ a Pavel RYCHLÝ. Finding Definitions in Large Corpora with Sketch Engine. In Nicoletta Calzolari (Conference Chair) et al. \textit{Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016)}. Portorož, Slovenia: European Language Resources Association (ELRA), 2016, s.~391-394. ISBN~978-2-9517408-9-1.

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