Difference between revisions of "User:Gor ar"
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[[User:Gor_ar/proposal_2017|My proposal for GSoC 2017]] |
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GSoC 2017 Proposal: UD and Apertium Integration. |
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== Contact information == |
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'''Name:''' Gor Arakelyan |
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'''Email:''' gor19973010@gmail.com |
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'''Skype:''' gor.arakelyan4 |
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== About me == |
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I am a second-year student in YSU (Yerevan State University) at the department of Informatics and Applied Mathematics. |
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I am interested in natural language processing, especially for low resource languages, like my native language Armenian. Apertium seems to be a perfect platform for that. |
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== Background == |
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The most important problem for Armenian NLP (and possibly for many others) is the lack of a properly annotated treebank. In order to help linguists to quickly annotate large amounts of text, an annotation tool with easy to use interface is required. I believe UD annotatrix is a very good tool to start with. |
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== Proposed solution == |
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Currently it lacks convenient UI to [https://github.com/jonorthwash/ud-annotatrix/issues/6 edit POS tags] or [https://github.com/jonorthwash/ud-annotatrix/issues/3 dependency relations]. I propose the following solutions: |
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* The simple textbox in UD annotatrix can be replaced by a more convenient rich code editor (like [https://codemirror.net CodeMirror]) |
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* Rich editor will provide autocompletion for UD specific tags (VERB, ADV, NOUN, Definite etc.) |
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* In the later stages we can make autocomplete more intelligent: |
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* - e.g. display only verb specific tags when POS is set to verb (tense) |
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* - use previously annotated data to provide suggestions |
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* Make UD annotatrix portable so it can be included in larger applications, e.g. in an app that uses a backend to save annotations |
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* Support [https://github.com/jonorthwash/ud-annotatrix/issues/8 multiword tokens] in the visualisation |
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== My experience == |
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I have been doing web development for 3 years now. Recently I worked on [https://github.com/YerevaNN/armtreebank an open source tool for corpus management] (currently used for Armenian only). It involved coding in HTML, JS and Python. |
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[[Category:GSoC 2017 Student Proposals]] |
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