# Watset: Automatic Induction of Synsets from a Graph of Synonyms

## TL;DR

Watset introduces a graph-based method for automatically inducing synsets from synonymy graphs and word embeddings, effectively handling ambiguity and outperforming existing methods on multiple datasets.

## Contribution

The paper proposes a novel meta-clustering approach that combines synonym graphs and word sense induction to automatically generate high-quality synsets.

## Key findings

- Outperforms five state-of-the-art methods in F-score
- Effective on datasets for English and Russian
- Handles ambiguous words through sense induction

## Abstract

This paper presents a new graph-based approach that induces synsets using synonymy dictionaries and word embeddings. First, we build a weighted graph of synonyms extracted from commonly available resources, such as Wiktionary. Second, we apply word sense induction to deal with ambiguous words. Finally, we cluster the disambiguated version of the ambiguous input graph into synsets. Our meta-clustering approach lets us use an efficient hard clustering algorithm to perform a fuzzy clustering of the graph. Despite its simplicity, our approach shows excellent results, outperforming five competitive state-of-the-art methods in terms of F-score on three gold standard datasets for English and Russian derived from large-scale manually constructed lexical resources.