Publication

Kamusi Pre:D – Lexicon-based source-side predisambiguation for MT and other text processing applications

2016
Working Papers

Abstract

Kamusi has been developing a system to analyze texts on the source side and present users with sense-specified dictionary options. Similarly to spellcheck, the user selects the intended meaning. We then use a multilingual lexical database to bridge to matching vocabulary in other languages. When paired with Freeling, additional pre-processing is possible for several languages. Integration with MT via Moses and Apertium is planned, but not yet undertaken. MWEs treatment is important. An MWE is lexicalized in the Kamusi database and marked for separability, with a definition and translation equivalents (one or more words) in other languages. When the initial term of an MWE appears in the source text, Pre:D queries the database and scans the sentence for all MWEs that could follow. The user can select the relevant MWE rather than the component words. A user can submit a missing sense or MWE for inclusion in the lexicon. Named entities can also be identified from data sources or by users and rendered appropriately across languages. When users agree, we will also use sense-tagged sentences for machine learning. A prototype of the core system is already functional.

Official source

https://infoscience.epfl.ch/entities/publication/3cc743a2-fdf0-4d8a-9aa9-e852fcb17156

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2016
Working Papers

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/3cc743a2-fdf0-4d8a-9aa9-e852fcb17156

About this result

Related concepts (32)

Word-sense disambiguation

Word-sense disambiguation (WSD) is the process of identifying which sense of a word is meant in a sentence or other segment of context. In human language processing and cognition, it is usually subconscious/automatic but can often come to conscious attention when ambiguity impairs clarity of communication, given the pervasive polysemy in natural language. In computational linguistics, it is an open problem that affects other computer-related writing, such as discourse, improving relevance of search engines, anaphora resolution, coherence, and inference.

Text mining

Text mining, text data mining (TDM) or text analytics is the process of deriving high-quality information from text. It involves "the discovery by computer of new, previously unknown information, by automatically extracting information from different written resources." Written resources may include websites, books, emails, reviews, and articles. High-quality information is typically obtained by devising patterns and trends by means such as statistical pattern learning. According to Hotho et al.

Translation

Translation is the communication of the meaning of a source-language text by means of an equivalent target-language text. The English language draws a terminological distinction (which does not exist in every language) between translating (a written text) and interpreting (oral or signed communication between users of different languages); under this distinction, translation can begin only after the appearance of writing within a language community.

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