Difference between revisions of "Task ideas for Google Code-in"

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|mentors=anakuz, fotonzade
|mentors=anakuz, fotonzade
|title=Syntactic trees
|title=Syntactic trees
|description=Pick up a text of ~200 words and make it's syntactic annotation as for Universal Dependencies treebank. UD Annotatrix can be used for visualisation. Consult with mentor about the language.
|description=Pick up a text of ~200 words and make its syntactic annotation as for Universal Dependencies treebank. UD Annotatrix can be used for visualisation. Consult with mentor about the language.
|tags=UD, trees, markup
|tags=UD, trees, markup
}}
}}
Line 538: Line 538:
|description=The man page for apertium-tagger is outdted, not mentioning some options the --help command does, like -x. They should be synced. See https://github.com/apertium/apertium/issues/10
|description=The man page for apertium-tagger is outdted, not mentioning some options the --help command does, like -x. They should be synced. See https://github.com/apertium/apertium/issues/10
|tags=C++
|tags=C++
}}

{{Taskidea
|type=Research
|mentors=ftyers
|title=Find out how to change eflomal to save alignment models
|description=Eflomal is a word aligner, that means that given a parallel corpus (sets of sentences in two languages) it can find the best alignment between the words in each language. At the moment it is not possible to save the model. The objective of this task is to find out how to save the model.
|tags=C, NLP
}}
}}


Line 551: Line 543:
|type=Code
|type=Code
|mentors=ftyers
|mentors=ftyers
|title=Change eflomal to save alignment models
|title=Port pragmatic segmenter core code to Python
|description=Pragmatic segmenter (https://github.com/diasks2/pragmatic_segmenter) is a sentence segmenter written in Ruby. The objective of this task is to port the core code to Python.
|description=Eflomal is a word aligner, that means that given a parallel corpus (sets of sentences in two languages) it can find the best alignment between the words in each language. At the moment it is not possible to save the model. The objective of this task is to change eflomal to have the option to save alignment models.
|tags=C, NLP
|tags=Python, Ruby
}}
}}


Line 559: Line 551:
|type=Code
|type=Code
|mentors=ftyers
|mentors=ftyers
|title=Port pragmatic segmenter core code to Python
|title=Port a language model from pragmatic segmenter to Python
|description=Pragmatic segmenter (https://github.com/diasks2/pragmatic_segmenter) is a sentence segmenter written in Ruby. The objective of this task is to port the core code to Python.
|description=Pragmatic segmenter (https://github.com/diasks2/pragmatic_segmenter) is a sentence segmenter written in Ruby. The objective of this task is to port a given language (e.g. Armenian) to Python.
|tags=Python, Ruby
|tags=Python, Ruby
|multi=21
}}
}}



{{Taskidea
{{Taskidea
|type=Code
|type=Code
|mentors=ftyers
|mentors=ftyers
|title=Port a language model from pragmatic segmenter to Python
|title=Write a language model for pragmatic segmenter in Python or Ruby
|description=Pragmatic segmenter (https://github.com/diasks2/pragmatic_segmenter) is a sentence segmenter written in Ruby. The objective of this task is to port a given language (e.g. Armenian) to Python.
|description=Pragmatic segmenter (https://github.com/diasks2/pragmatic_segmenter) is a sentence segmenter written in Ruby. The objective of this task is to write a language model for a new language.
|tags=Python, Ruby
|tags=Python, Ruby
|multi=21
|multi=21

Revision as of 00:45, 21 October 2018

This is the task ideas page for Google Code-in, here you can find ideas on interesting tasks that will improve your knowledge of Apertium and help you get into the world of open-source development.

The people column lists people who you should get in contact with to request further information. All tasks are 2 hours maximum estimated amount of time that would be spent on the task by an experienced developer, however:

  1. this is the time expected to take by an experienced developer, you may find that you spend more time on the task because of the learning curve.

Categories:

  • code: Tasks related to writing or refactoring code
  • documentation: Tasks related to creating/editing documents and helping others learn more
  • research: Tasks related to community management, outreach/marketting, or studying problems and recommending solutions
  • quality: Tasks related to testing and ensuring code is of high quality.
  • design: Tasks related to user experience research or user interface design and interaction

Clarification of "multiple task" types

  • multi = number of students who can do a given task
  • dup = number of times a student can do the same task

You can find descriptions of some of the mentors here.

Task ideas

Counts

Last updated by Sushain (talk) 19:22, 15 September 2018 (CEST).

Category Count
code 35
documentation 5
research 10
quality 10
design 5
Total 53
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