Podrobný výpis o publikaci

STARÝ, Michal, Zuzana NEVĚŘILOVÁ a Jakub VALČÍK. Multilingual Recognition of Temporal Expressions. In Aleš Horák. Proceedings of the Fourteenth Workshop on Recent Advances in Slavonic Natural Language Processing, RASLAN 2020. Brno: Tribun EU, 2020, s. 67-78. ISBN 978-80-263-1600-8.

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Základní údaje
Originální název	Multilingual Recognition of Temporal Expressions
Autoři	STARÝ, Michal (203 Česká republika, garant, domácí), Zuzana NEVĚŘILOVÁ (203 Česká republika, domácí) a Jakub VALČÍK (203 Česká republika).
Vydání	Brno, Proceedings of the Fourteenth Workshop on Recent Advances in Slavonic Natural Language Processing, RASLAN 2020, od s. 67-78, 12 s. 2020.
Nakladatel	Tribun EU

Další údaje
Originální 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"
WWW	Domovská stránka sborníku PDF ve sborníku
Kód RIV	RIV/00216224:14330/20:00117840
Organizační jednotka	Fakulta informatiky
ISBN	978-80-263-1600-8
ISSN	2336-4289
UT WoS	000655471300007
Klíčová slova anglicky	temporal expressions; multilingual; date recognition
Štítky	date recognition, multilingual, temporal expressions
Příznaky	Mezinárodní význam
Změnil	Změnil: Mgr. Michal Petr, učo 65024. Změněno: 16. 5. 2022 15:10.

Anotace
The paper presents a multilingual approach to temporal expression recognition (TER) using existing tools and their combination. We observe that the rules based methods perform well on documents using wellformed temporal expressions in a narrower domain (e.g., news), while data driven methods are more stable within less standard language and texts across domains. With combination of the two approaches, we achieved F1 of 0.73 and 0.9 for strict and relaxed evaluations respectively on one English dataset. Although these results do not achieve the state-of-the-art on English, the same method outperformed the state-of-the-art results in a multilingual setting not only in recall but also in F1. We see this as a strong indication that combining rule based systems with data driven models such as BERT is a valid approach to improve the overall performance in TER, especially for languages other than English. Further observations indicate that in the domain of office documents, the combined method is able to recognize general temporal expressions as well as domain specific ones (e.g., those used in financial documents).

Anotace

The paper presents a multilingual approach to temporal expression recognition (TER) using existing tools and their combination. We observe that the rules based methods perform well on documents using wellformed temporal expressions in a narrower domain (e.g., news), while data driven methods are more stable within less standard language and texts across domains. With combination of the two approaches, we achieved F1 of 0.73 and 0.9 for strict and relaxed evaluations respectively on one English dataset. Although these results do not achieve the state-of-the-art on English, the same method outperformed the state-of-the-art results in a multilingual setting not only in recall but also in F1. We see this as a strong indication that combining rule based systems with data driven models such as BERT is a valid approach to improve the overall performance in TER, especially for languages other than English. Further observations indicate that in the domain of office documents, the combined method is able to recognize general temporal expressions as well as domain specific ones (e.g., those used in financial documents).

Návaznosti
LM2018101, projekt VaV	Název: Digitální výzkumná infrastruktura pro jazykové technologie, umění a humanitní vědy (Akronym: LINDAT/CLARIAH-CZ)
LM2018101, projekt VaV	Investor: Ministerstvo školství, mládeže a tělovýchovy ČR, LINDAT/CLARIAH-CZ - Digitální výzkumná infrastruktura pro jazykové technologie, umění a humanitní vědy