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 Unfortunately, wordnets get outdated, and producing or updatingwordnets can be slow and costly in terms of time and resources.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

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