Pregled bibliografske jedinice broj: 864193
Cro36WSD: A Lexical Sample for Croatian Word Sense Disambiguation
Cro36WSD: A Lexical Sample for Croatian Word Sense Disambiguation // Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016) / Nicoletta Calzolari, Khalid Choukri, Thierry Declerck, Sara Goggi, Marko Grobelnik, Bente Maegaard, Joseph Mariani, Helene Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis (ur.).
Portorož: European Language Resources Association (ELRA), 2016. str. 1689-1694 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 864193 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Cro36WSD: A Lexical Sample for Croatian Word Sense Disambiguation
Autori
Alagić, Domagoj ; Šnajder, Jan
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016)
/ Nicoletta Calzolari, Khalid Choukri, Thierry Declerck, Sara Goggi, Marko Grobelnik, Bente Maegaard, Joseph Mariani, Helene Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis - Portorož : European Language Resources Association (ELRA), 2016, 1689-1694
ISBN
978-2-9517408-9-1
Skup
Tenth International Conference on Language Resources and Evaluation (LREC 2016)
Mjesto i datum
Portorož, Slovenija, 23.05.2016. - 28.05.2016
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
Word Sense Disambiguation ; Semantics
Sažetak
We introduce Cro36WSD, a freely-available medium-sized lexical sample for Croatian word sense disambiguation (WSD). Cro36WSD comprises 36 words: 12 adjectives, 12 nouns, and 12 verbs, balanced across both frequency bands and polysemy levels. We adopt the multi-label annotation scheme in the hope of lessening the drawbacks of discrete sense inventories and obtaining more realistic annotations from human experts. Sense-annotated data is collected through multiple annotation rounds to ensure high-quality annotations: with an 115 person-hours effort we reached an inter-annotator agreement score of 0.877. We analyze the obtained data and perform a correlation analysis between several relevant variables, including word frequency, number of senses, sense distribution skewness, average annotation time, and the observed inter-annotator agreement (IAA). Using the obtained data, we compile multi- and single-labeled dataset variants using different label aggregation schemes. Finally, we evaluate three different baseline WSD models on both dataset variants and report on the insights gained. We make both dataset variants freely available.
Izvorni jezik
Engleski
Znanstvena područja
Računarstvo
POVEZANOST RADA
Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb