---
title: "Word Sense Disambiguation for All Words without Hard Labor"
authors:
  - "Zhi Zhong"
  - "Hwee Tou Ng"
doi: ""
url: "https://ijcai.org/proceedings/2009/270"
pdf: "https://ijcai.org/proceedings/2009/0270.pdf"
venue: "Proceedings of the Twenty-First International Joint Conference on Artificial Intelligence"
year: 2009
pages: "1616-1621"
track: ""
keywords:
---

# Word Sense Disambiguation for All Words without Hard Labor

Zhi Zhong, Hwee Tou Ng

*Proceedings of the Twenty-First International Joint Conference on Artificial Intelligence*, pages 1616-1621.

## Abstract

While the most accurate word sense disambiguation systems are built using supervised learning from sense-tagged data, scaling them up to all words of a language has proved elusive, since preparing a sense-tagged corpus for all words of a language is time-consuming and human labor intensive. In this paper, we propose and implement a completely automatic approach to scale up word sense disambiguation to all words of English. Our approach relies on English-Chinese parallel corpora, English-Chinese bilingual dictionaries, and automatic methods of finding synonyms of Chinese words. No additional human sense annotations or word translations are needed. We conducted a large-scale empirical evaluation on more than 29,000 noun tokens in English texts annotated in OntoNotes 2.0, based on its coarse-grained sense inventory. The evaluation results show that our approach is able to achieve high accuracy, outperforming the first-sense baseline and coming close to a prior reported approach that requires manual human efforts to provide Chinese translations of English senses.Zhi Zhong, Hwee Tou Ng