Language resources such as wordnets remain indispensable tools for different
natural language tasks and applications. However, for low-resource languages
such as Filipino, existing wordnets are old and outdated, and producing new
ones may be slow and costly in terms of time and resources. In this paper, we
propose an automatic method for constructing a wordnet from scratch using only
an unlabeled corpus and a sentence embeddings-based language model. Using this,
we produce FilWordNet, a new wordnet that supplants and improves the outdated
Filipino WordNet. We evaluate our automatically-induced senses and synsets by
matching them with senses from the Princeton WordNet, as well as comparing the
synsets to the old Filipino WordNet. We empirically show that our method can
induce existing, as well as potentially new, senses and synsets automatically
without the need for human supervision.

该研究提出了一种基于句子嵌入语言模型的自动构建词网的方法，利用未标记的语料库构建了 FilWordNet，该方法在不需人为监督的情况下可以自动感知词义和同义词集。