Using a Probabilistic Class-Based Lexicon for Lexical Ambiguity Resolution
Abstract
This paper presents the use of probabilistic class-based lexica for disambiguation in target-word selection. Our method employs minimal but precise contextual information for disambiguation. That is, only information provided by the target-verb, enriched by the condensed information of a probabilistic class-based lexicon, is used. Induction of classes and fine-tuning to verbal arguments is done in an unsupervised manner by EM-based clustering techniques. The method shows promising results in an evaluation on real-world translations.
- Publication:
-
arXiv e-prints
- Pub Date:
- August 2000
- DOI:
- 10.48550/arXiv.cs/0008035
- arXiv:
- arXiv:cs/0008035
- Bibcode:
- 2000cs........8035P
- Keywords:
-
- Computer Science - Computation and Language;
- I.2.6;
- I.2.7
- E-Print:
- 7 pages, uses colacl.sty