Výsledky vyhledávání - "Esme Manandise"

From Tax Compliance in Natural Language to Executable Calculations: Combining Lexical-grammar-based Parsing and Machine Learning

Autor: Esme Manandise, Saikat Mukherjee, Conrad de Peuter

Publikováno v: FLAIRS Conference

Regulatory agencies publish tax-compliance content written in natural language intended for human consumption. There has been very little work on automated methods for interpreting this content and for generating executable calculations from it. In t

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::9e9361295f2e3cfcc7c39e2be8b234c1
https://doi.org/10.32473/flairs.v34i1.128351

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The Bare Necessities: Increasing Lexical Coverage for Multi-Word Domain Terms with Less Lexical Data

Autor: Esme Manandise, Benjamin P. Segal, Branimir Boguraev

Publikováno v: MWE@NAACL-HLT

We argue that many multi-word domain terms are not (and should not be regarded as) strictly atomic, especially from a parser’s point of view. We introduce the notion of Lexical Kernel Units (LKUs), and discuss some of their essential properties. LK

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::864047dab1518f1a5da97f5417ea8c41
https://doi.org/10.3115/v1/w15-0910

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Morphology to the Rescue Redux: Resolving Borrowings and Code-Mixing in Machine Translation

Autor: Claudia Gdaniec, Esme Manandise

Publikováno v: Systems and Frameworks for Computational Morphology ISBN: 9783642231377
SFCM

In the IBM LMT machine translation system, derivational morphological rules recognize and analyze words that are not found in its source lexicons, and generate default transfers for these unlisted words. Unfound words with no inflectional or derivati

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::679abfb5b23ad154e38d02ccb3e3c219
https://doi.org/10.1007/978-3-642-23138-4_6

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Using Word Formation Rules to Extend MT Lexicons

Autor: Claudia Gdaniec, Esme Manandise

Publikováno v: Machine Translation: From Research to Real Users ISBN: 9783540442820
AMTA

In the IBM LMT Machine Translation (MT) system, a built-in strategy provides lexical coverage of a particular subset of words that are not listed in its bilingual lexicons. The recognition and coding of these words and their transfer generation is ba

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::1cd31389f18248dcd3ab9dc450451e57
https://doi.org/10.1007/3-540-45820-4_7

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