Towards Automatic Construction of Filipino WordNet: Word Sense Induction and Synset Induction Using Sentence Embeddings

TL;DR

This paper presents a novel method for automatically constructing Filipino WordNet by inducing word senses and synsets using only unlabeled corpora and sentence embeddings, addressing resource scarcity.

Contribution

It introduces a new approach for word sense and synset induction that requires minimal resources, specifically tailored for low-resource languages like Filipino.

Findings

30% of induced senses are valid

40% of induced synsets are valid

20% of synsets are novel

Abstract

Wordnets are indispensable tools for various natural language processing applications. Unfortunately, wordnets get outdated, and producing or updating wordnets can be slow and costly in terms of time and resources. This problem intensifies for low-resource languages. This study proposes a method for word sense induction and synset induction using only two linguistic resources, namely, an unlabeled corpus and a sentence embeddings-based language model. The resulting sense inventory and synonym sets can be used in automatically creating a wordnet. We applied this method on a corpus of Filipino text. The sense inventory and synsets were evaluated by matching them with the sense inventory of the machine translated Princeton WordNet, as well as comparing the synsets to the Filipino WordNet. This study empirically shows that the 30% of the induced word senses are valid and 40% of the induced synsets are valid in which 20% are novel synsets.