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Turkic MT Improvements GSoC2019 report

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(Lexical Selection)
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==Lexical Selection==
 
==Lexical Selection==
To determine in which context which translation of a given lemma would be selected, lexical selection is employed. Currently uig-tur has 35 lexsel rules.
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To determine in which context which translation of a given lemma would be selected, lexical selection is employed.

Revision as of 11:11, 23 August 2019

This aim of this project was improving the following language pairs of Apertium: tur->uig, uzb->tur, kir->tur, tat->tur.

Contents

Commits

My commits can be found [here]. You can also download my work as a [ zip file].

Transfer

Transfer rules were written for tur->uig and uzb->tur, using Regression Tests. They can be found here: Uighur and Uzbek.


Corpora and Coverage

L Wiki Bible
Tur-Uig 53505239 words, 82.3% cov 178233 words, 93.0% cov
Uzb-Tur 12730161 words, 80.8% cov 184447 words, 81.1% cov
Kir-Tur 11435418 words, 82.5% cov 184808 words, 92.0% cov
Tat-Tur -- 178220 words, 91.4% cov


Disambiguation

To correctly discern the lemma and the morphology so as to be translated correctly into the target language, Apertium uses Constraint Grammar (CG). Currently Uyghur has about 45 CG rules for disambiguation.


Lexical Selection

To determine in which context which translation of a given lemma would be selected, lexical selection is employed.

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