A Multi-Pass Sieve Coreference Resolution for Indonesian

Valentina Kania Prameswara Artari, Rahmad Mahendra, Meganingrum Arista Jiwanggi, Adityo Anggraito, Indra Budi


Abstract
Coreference resolution is an NLP task to find out whether the set of referring expressions belong to the same concept in discourse. A multi-pass sieve is a deterministic coreference model that implements several layers of sieves, where each sieve takes a pair of correlated mentions from a collection of non-coherent mentions. The multi-pass sieve is based on the principle of high precision, followed by increased recall in each sieve. In this work, we examine the portability of the multi-pass sieve coreference resolution model to the Indonesian language. We conduct the experiment on 201 Wikipedia documents and the multi-pass sieve system yields 72.74% of MUC F-measure and 52.18% of BCUBED F-measure.
Anthology ID:
2021.ranlp-1.10
Volume:
Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2021)
Month:
September
Year:
2021
Address:
Held Online
Editors:
Ruslan Mitkov, Galia Angelova
Venue:
RANLP
SIG:
Publisher:
INCOMA Ltd.
Note:
Pages:
79–85
Language:
URL:
https://aclanthology.org/2021.ranlp-1.10
DOI:
Bibkey:
Cite (ACL):
Valentina Kania Prameswara Artari, Rahmad Mahendra, Meganingrum Arista Jiwanggi, Adityo Anggraito, and Indra Budi. 2021. A Multi-Pass Sieve Coreference Resolution for Indonesian. In Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2021), pages 79–85, Held Online. INCOMA Ltd..
Cite (Informal):
A Multi-Pass Sieve Coreference Resolution for Indonesian (Artari et al., RANLP 2021)
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PDF:
https://aclanthology.org/2021.ranlp-1.10.pdf