A sequence labelling approach for automatic analysis of ello: tagging pronouns, antecedents, and connective phrases
Authors
Parodi, GiovanniEvans, Richard
Ha, Le An
Mitkov, Ruslan
Julio, Cristóbal
Olivares-López, Raúl Ignacio
Issue Date
2021-09-04
Metadata
Show full item recordAbstract
Encapsulators are linguistic units which establish coherent referential connections to the preceding discourse in a text. In this paper, we address the challenge of automatically analysing the pronominal encapsulator ello in Spanish text. Our method identifies, for each occurrence, the antecedent of the pronoun (including its grammatical type), the connective phrase which combines with the pronoun to express a discourse relation linking the antecedent text segment to the following text segment, and the type of semantic relation expressed by the complex discourse marker formed by the connective phrase and pronoun. We describe our annotation of a corpus to inform the development of our method and to finetune an automatic analyser based on bidirectional encoder representation transformers (BERT). On testing our method, we find that it performs with greater accuracy than three baselines (0.76 for the resolution task), and sets a promising benchmark for the automatic annotation of occurrences of the pronoun ello, their antecedents, and the semantic relations between the two text segments linked by the connective in combination with the pronoun.Citation
Parodi, G., Evans, R., Ha, L.A., Mitkov, R., Vergara, C.J.J., Olivares-López,, R.I. (2022) A sequence labelling approach for automatic analysis of ello: tagging pronouns, antecedents, and connective phrases. Language Resources and Evaluation 56, pp. 139–164. https://doi.org/10.1007/s10579-021-09559-zPublisher
SpringerJournal
Language Resources and EvaluationAdditional Links
https://link.springer.com/article/10.1007%2Fs10579-021-09559-zType
Journal articleLanguage
enDescription
This is an accepted manuscript of an article published by Springer in Language Resources and Evaluation on 04/09/2021, available online: https://doi.org/10.1007/s10579-021-09559-z The accepted version of the publication may differ from the final published version.ISSN
1574-020Xae974a485f413a2113503eed53cd6c53
10.1007/s10579-021-09559-z
Scopus Count
Except where otherwise noted, this item's license is described as https://creativecommons.org/licenses/by-nc-nd/4.0/