Paper Info
Title
An algorithm for finding noun phrase correspondences in bilingual corpora
Abstract
The paper describes an algorithm that employs English and French text taggers to associate noun phrases in an aligned bilingual corpus. The taggers provide part-of-speech categories which are used by finite-state recognizers to extract simple noun phrases for both languages. Noun phrases are then mapped to each other using an iterative re-estimation algorithm that bears similarities to the Baum-Welch algorithm which is used for training the taggers. The algorithm provides an alternative to other approaches for finding word correspondences, with the advantage that linguistic structure is incorporated. Improvements to the basic algorithm are described, which enable context to be accounted for when constructing the noun phrase mappings.
Year
DOI
Venue
1993
10.3115/981574.981577
ACL
Keywords
Field
DocType
french text taggers,basic algorithm,finite-state recognizers,simple noun phrase,associate noun phrase,noun phrase correspondence,bilingual corpus,noun phrase mapping,baum-welch algorithm,noun phrase,iterative re-estimation algorithm,part of speech,baum welch
Noun phrase,Determiner phrase,Computer science,Noun,Algorithm,Speech recognition,Natural language processing,Artificial intelligence
Conference
Volume
Citations 
PageRank 
P93-1
108
25.99
References 
Authors
6
1
Search Limit
100108
Name
Order
Citations
PageRank
Julian Kupiec11061381.10