KMI-Panlingua-IITKGP @SIGTYP2020: Exploring rules and hybrid systems for automatic prediction of typological features

Ritesh Kumar, Deepak Alok, Akanksha Bansal, Bornini Lahiri, Atul Kr. Ojha


Abstract
This paper enumerates SigTyP 2020 Shared Task on the prediction of typological features as performed by the KMI-Panlingua-IITKGP team. The task entailed the prediction of missing values in a particular language, provided, the name of the language family, its genus, location (in terms of latitude and longitude coordinates and name of the country where it is spoken) and a set of feature-value pair are available. As part of fulfillment of the aforementioned task, the team submitted 3 kinds of system - 2 rule-based and one hybrid system. Of these 3, one rule-based system generated the best performance on the test set. All the systems were ‘constrained’ in the sense that no additional dataset or information, other than those provided by the organisers, was used for developing the systems.
Anthology ID:
2020.sigtyp-1.2
Volume:
Proceedings of the Second Workshop on Computational Research in Linguistic Typology
Month:
November
Year:
2020
Address:
Online
Venues:
EMNLP | SIGTYP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
12–16
Language:
URL:
https://www.aclweb.org/anthology/2020.sigtyp-1.2
DOI:
10.18653/v1/2020.sigtyp-1.2
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PDF:
http://aclanthology.lst.uni-saarland.de/2020.sigtyp-1.2.pdf