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Accenture at CheckThat! 2021: Interesting claim identification and ranking with contextually sensitive lexical training data augmentation ...
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Correcting Errors in Digital Lexicographic Resources Using a Dictionary Manipulation Language ...
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Abstract:
We describe a paradigm for combining manual and automatic error correction of noisy structured lexicographic data. Modifications to the structure and underlying text of the lexicographic data are expressed in a simple, interpreted programming language. Dictionary Manipulation Language (DML) commands identify nodes by unique identifiers, and manipulations are performed using simple commands such as create, move, set text, etc. Corrected lexicons are produced by applying sequences of DML commands to the source version of the lexicon. DML commands can be written manually to repair one-off errors or generated automatically to correct recurring problems. We discuss advantages of the paradigm for the task of editing digital bilingual dictionaries. ... : 5 pages, 3 figures, 1 table; appeared in Proceedings of Electronic Lexicography in the 21st Century (eLex), November 2011 ...
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Keyword:
Computation and Language cs.CL; FOS Computer and information sciences
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URL: https://dx.doi.org/10.48550/arxiv.1410.7787 https://arxiv.org/abs/1410.7787
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A random forest system combination approach for error detection in digital dictionaries ...
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Detecting Structural Irregularity in Electronic Dictionaries Using Language Modeling ...
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A random forest system combination approach for error detection in digital dictionaries
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Correcting Errors in Digital Lexicographic Resources Using a Dictionary Manipulation Language ...
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Detecting Structural Irregularity in Electronic Dictionaries Using Language Modeling ...
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Correcting Errors in Digital Lexicographic Resources Using a Dictionary Manipulation Language
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Detecting Structural Irregularity in Electronic Dictionaries Using Language Modeling
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Error Correction for Arabic Dictionary Lookup
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In: Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC 2010), Valetta, 17 - 23 May 2010 (2010), 263-268
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IDS OBELEX meta
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Unsupervised Morphology Induction for Part-of-speech-tagging
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In: University of Pennsylvania Working Papers in Linguistics (2006)
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