D 2016

Multilingual CPA: Linking Verb Patterns across Languages

BAISA, Vít, Sara MOŽE and Irene RENAU

Basic information

Original name

Multilingual CPA: Linking Verb Patterns across Languages

Authors

BAISA, Vít (203 Czech Republic, guarantor, belonging to the institution), Sara MOŽE (705 Slovenia) and Irene RENAU (724 Spain)

Edition

Tbilisi, Proceedings of the XVII EURALEX International congress, p. 410-417, 8 pp. 2016

Publisher

Ivane Javakhishvili Tbilisi State University

Other information

Language

English

Type of outcome

Stať ve sborníku

Field of Study

10201 Computer sciences, information science, bioinformatics

Country of publisher

Georgia

Confidentiality degree

není předmětem státního či obchodního tajemství

Publication form

electronic version available online

RIV identification code

RIV/00216224:14330/16:00090692

Organization unit

Faculty of Informatics

ISBN

978-9941-13-542-2

UT WoS

000392695200044

Keywords in English

Corpus Pattern Analysis; corpus lexicography; multilingual resources; verb patterns

Tags

International impact, Reviewed
Změněno: 20/7/2018 14:41, Mgr. Michal Petr

Abstract

V originále

This paper presents the results of a pilot study in linking corresponding English and Spanish verb patterns using both automatic and manual procedures. Our work is rooted in Corpus Pattern Analysis (CPA) (Hanks 2004, 2013), a corpus-driven technique that was used in the creation of existing monolingual pattern dictionaries of English and Spanish verbs, which were used in our experiment to design a gold standard of manually annotated verb pattern pairs. Research in CPA has inspired parallel projects in English, Spanish, Italian and German. Our study represents the first attempt to build a multilingual lexical resource by linking verb patterns in these languages. Verb have special difficulties related to grammar and argument structure that we do not find in other parts-of-speech, and for that reason we think that it is necessary to create a specific resource for them. After applying the automatic matching to a set of 87 Spanish verbs linked to 176 English verbs, an evaluation of a random selection of 50 of these pairs show 80% precision

Links

7F14047, research and development project
Name: Harvesting big text data for under-resourced languages (Acronym: HaBiT)
Investor: Ministry of Education, Youth and Sports of the CR