Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
102 tokens/sec
GPT-4o
59 tokens/sec
Gemini 2.5 Pro Pro
43 tokens/sec
o3 Pro
6 tokens/sec
GPT-4.1 Pro
50 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Don't Neglect the Obvious: On the Role of Unambiguous Words in Word Sense Disambiguation (2004.14325v3)

Published 29 Apr 2020 in cs.CL

Abstract: State-of-the-art methods for Word Sense Disambiguation (WSD) combine two different features: the power of pre-trained LLMs and a propagation method to extend the coverage of such models. This propagation is needed as current sense-annotated corpora lack coverage of many instances in the underlying sense inventory (usually WordNet). At the same time, unambiguous words make for a large portion of all words in WordNet, while being poorly covered in existing sense-annotated corpora. In this paper, we propose a simple method to provide annotations for most unambiguous words in a large corpus. We introduce the UWA (Unambiguous Word Annotations) dataset and show how a state-of-the-art propagation-based model can use it to extend the coverage and quality of its word sense embeddings by a significant margin, improving on its original results on WSD.

User Edit Pencil Streamline Icon: https://streamlinehq.com
Authors (2)
  1. Daniel Loureiro (12 papers)
  2. Jose Camacho-Collados (58 papers)
Citations (11)

Summary

We haven't generated a summary for this paper yet.