Czech Dataset for Cross-lingual Subjectivity Classification

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F22%3A43965946" target="_blank" >RIV/49777513:23520/22:43965946 - isvavai.cz</a>

Result on the web

<a href="https://aclanthology.org/2022.lrec-1.148/" target="_blank" >https://aclanthology.org/2022.lrec-1.148/</a>

DOI - Digital Object Identifier

—

Result language

angličtina

Original language name

Czech Dataset for Cross-lingual Subjectivity Classification

Original language description

In this paper, we introduce a new Czech subjectivity dataset of 10k manually annotated subjective and objective sentences from movie reviews and descriptions. Our prime motivation is to provide a reliable dataset that can be used with the existing English dataset as a benchmark to test the ability of pre-trained multilingual models to transfer knowledge between Czech and English and vice versa. Two annotators annotated the dataset reaching 0.83 of the Cohen’s kappa inter-annotator agreement. To the best of our knowledge, this is the first subjectivity dataset for the Czech language. We also created an additional dataset that consists of 200k automatically labeled sentences. Both datasets are freely available for research purposes. Furthermore, we fine-tune five pre-trained BERT-like models to set a monolingual baseline for the new dataset and we achieve 93.56% of accuracy. We fine-tune models on the existing English dataset for which we obtained results that are on par with the current state-of-the-art results. Finally, we perform zero-shot cross-lingual subjectivity classification between Czech and English to verify the usability of our dataset as the cross-lingual benchmark. We compare and discuss the cross-lingual and monolingual results and the ability of multilingual models to transfer knowledge between languages.

Czech name

—

Czech description

—

Type

D - Article in proceedings

CEP classification

—

OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

—

Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2022

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Proceedings of the Thirteenth Language Resources and Evaluation Conference

ISBN

979-10-95546-72-6

ISSN

—

e-ISSN

—

Number of pages

11

Pages from-to

1381-1391

Publisher name

European Language Resources Association

Place of publication

Marseille, France

Event location

Marseille, France

Event date

Jun 20, 2022

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

000889371701052