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Bilingual Lexicon Construction Using Large Corpora
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Abstract:
This paper introduces a method for learning bilingual term and sentence level alignments for the purpose of building lexicons. Combining statistical techniques with linguistic knowledge, a general algorithm is developed for learning term and sentence alignments from large bilingual corpora with high accuracy. This is achieved through the use of filtered linguistic feedback between term and sentence alignment processes. An implementation of this algorithm, TAG-ALIGN, is evaluated against approaches similar to [Brown et al. 1993] that apply Bayesian techniques for term alignment, and [Gale and Church 1991] a dynamic programming method for aligning sentences. The ultimate goal is to produce large bilingual lexicons with a high degree of accuracy from potentially noisy corpora. (Also cross-referenced as UMIACS-TR-97-50)
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URL: http://hdl.handle.net/1903/832
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42 |
Using WordNet to Posit Hierarchical Structure in Levin's Verb Classes
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43 |
Automatic Extraction of Semantic Classes from Syntactic Information in Online Resources
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44 |
Development of Interlingual Lexical Conceptual Structures with Syntactic Markers for Machine Translation
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45 |
Lexical Selection for Cross-Language Applications: Combining LCS with WordNet
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46 |
A Thematic Hierarchy for Efficient Generation from Lexical-Conceptual Structure
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47 |
Aspectual Modifications to a LCS Database for NLP Applications
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48 |
Toward Compact Monotonically Compositional Interlingua Using Lexical Aspect
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49 |
Development of Cross-Linguistic Syntactic and Semantic Parameters for Parsing and Generation
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50 |
A Comparative Study of Knowledge-Based Approaches for Cross-Language Information Retrieval
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52 |
Aspectual Modifications to a LCS Database for NLP Applications
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In: DTIC (1997)
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53 |
Toward Compact Monotonically Compositional Interlingua Using Lexical Aspect
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In: DTIC (1997)
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54 |
Using WordNet to Posit Hierarchical Structure in Levin's Verb Classes
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In: DTIC (1997)
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