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Hits 61 – 80 of 157

61
Domain-Specific Term-List Expansion Using Existing Linguistic Resources
In: DTIC (2002)
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62
Improved Word-Level Alignment: Injecting Knowledge about MT Divergences
In: DTIC (2002)
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63
Handling Translation Divergences: Combining Statistical and Symbolic Techniques in Generation-Heavy Machine Translation
In: DTIC (2002)
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64
Creating Parsing Lexicons from Semantic Lexicons Automatically and Its Applications
In: DTIC (2002)
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65
Constraints on the Generation of Tense, Aspect, and Connecting Words from Temporal Expressions
In: DTIC (2002)
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66
Construction of a Chinese-English Verb Lexicon for Embedded Machine Translation in Cross-Language Information Retrieval
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67
Domain-Specific Term-List Expansion Using Existing Linguistic Resources
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68
Constraints on the Generation of Tense, Aspect, and Connecting Words from Temporal Expressions
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69
Handling Translation Divergences: Combining Statistical and Symbolic Techniques in Generation-Heavy Machine Translation
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70
Handling Translation Divergences in Generation-Heavy Hybrid Machine Translation
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71
Machine translation
Maegaard, Bente (Hrsg.); Bel, Núria (Mitarb.); Dorr, Bonnie Jean (Mitarb.)...
In: Multilingual information management. - Pisa [u.a.] : Ist. Ed. e Poligrafici Internazionli (2001), 81-103
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72
Efficient Language Independent Generation from Lexical Conceptual Structure
In: DTIC (2001)
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73
Building a Chinese-English Mapping Between Verb Concepts for Multilingual Applications
In: DTIC (2001)
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74
Large Scale Language Independent Generation Using Thematic Hierarchies
In: DTIC (2001)
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75
Mapping Lexical Entries in a Verbs Database to WordNet Senses
In: DTIC (2001)
Abstract: This paper describes automatic techniques for mapping 9611 entries in a database of English verbs to WordNet senses. The verbs were initially grouped into 491 classes based on syntactic categories. Mapping these classified verbs into WordNet senses provides a resource that may be used for disambiguation in multilingual applications such as machine translation and cross-language information retrieval. Our techniques make use of (1) a training set of 1791 disambiguated entries representing 1442 verb entires from 167 of the categories; (2) word sense probabilities based on frequency counts in a previously tagged corpus; (3) semantic similarity of WordNet senses for verbs within the same class (4) probabilistic correlations between WordNet data and attributes of the verb classes. The best results achieved 72% precision and 58% recall., versus a lower bound of 62% precision and 38% recall for assigning the most frequently occurring WordNet sense, and an upper bound of 87% precision and 75% recall for human judgment. ; Additional report no. UMIACS-TR-2001-18.
Keyword: *DATA BASES; *ENGLISH LANGUAGE; *LEXICOGRAPHY; *MACHINE TRANSLATION; *VERBS DATABASES; AUTOMATIC; CORRELATION; COUNTING METHODS; Cybernetics; FREQUENCY; HUMANS; JUDGEMENT(PSYCHOLOGY); Linguistics; PROBABILITY
URL: http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA458750
http://www.dtic.mil/docs/citations/ADA458750
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76
Spanish Language Processing at University of Maryland: Building Infrastructure for Multilingual Applications
In: DTIC (2001)
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77
Mapping WorldNet Senses to a Lexical Database of Verbs
In: DTIC (2001)
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78
Efficient Language Independent Generation from Lexical Conceptual Structures
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79
Lexical Resource Integration across the Syntax-Semantics Interface
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80
Mapping Lexical Entries in a Verbs Database to WordNet Senses
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