Abstract
In languages like Arabic, Chinese, Italian, Japanese, Korean, Portuguese, Spanish, and many others, predicate arguments in certain syntactic positions are not realized instead of being realized as overt pronouns, and are thus called zero- or null-pronouns. Identifying and resolving such omitted arguments is crucial to machine translation, information extraction and other NLP tasks, but depends heavily on semantic coherence and lexical relationships. We propose a BERT-based cross-lingual model for zero pronoun resolution, and evaluate it on the Arabic and Chinese portions of OntoNotes 5.0. As far as we know, ours is the first neural model of zero-pronoun resolution for Arabic; and our model also outperforms the state-of-the-art for Chinese. In the paper we also evaluate BERT feature extraction and fine-tune models on the task, and compare them with our model. We also report on an investigation of BERT layers indicating which layer encodes the most suitable representation for the task.- Anthology ID:
- 2020.lrec-1.11
- Volume:
- Proceedings of the Twelfth Language Resources and Evaluation Conference
- Month:
- May
- Year:
- 2020
- Address:
- Marseille, France
- Editors:
- Nicoletta Calzolari, Frédéric Béchet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Hélène Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis
- Venue:
- LREC
- SIG:
- Publisher:
- European Language Resources Association
- Note:
- Pages:
- 90–98
- Language:
- English
- URL:
- https://aclanthology.org/2020.lrec-1.11
- DOI:
- Cite (ACL):
- Abdulrahman Aloraini and Massimo Poesio. 2020. Cross-lingual Zero Pronoun Resolution. In Proceedings of the Twelfth Language Resources and Evaluation Conference, pages 90–98, Marseille, France. European Language Resources Association.
- Cite (Informal):
- Cross-lingual Zero Pronoun Resolution (Aloraini & Poesio, LREC 2020)
- PDF:
- https://preview.aclanthology.org/emnlp-22-attachments/2020.lrec-1.11.pdf