UC-B1

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(The CorpusA2)
(The CorpusA2)
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Revision as of 13:10, 5 September 2012

The CorpusA2 is an experimental corpus used to prepare the initial versions of the grammar for sentence-based UNLization and NLization, using IAN and EUGENE, respectively. It comprises 5 texts in English and their corresponding graphs in UNL, and is supposed to cover very basic linguistic phenomena.

Contents

The CorpusA2

Text Title English* UNL** Number of sentences
Text I The Hare and the Tortoise corpusA2_text1_eng.txt to be provided soon 13
Text II to be provided soon to be provided soon to be provided soon
Text III to be provided soon to be provided soon to be provided soon
Text IV to be provided soon to be provided soon to be provided soon
Text V to be provided soon to be provided soon to be provided soon

*To be manually translated to your target language in order to be used as the input for UNLization (IAN)
**To be used as the input for NLization (EUGENE)

Goals

  1. To provide the dictionary and grammars necessary to UNLize your translated version of the CorpusA2 (with IAN)
  2. To provide the dictionary and grammars necessary to NLize, to your target language, the UNL version of the CorpusA2 (with EUGENE)

Methodology

In order to prepare the dictionaries and grammars to deal with the CorpusA2, follow the steps below for each text:

UNLization

  1. Corpus
    1. Translate (manually) the sentences of the CorpusA2 from English into your native language. Be as close as possible to the original, and provide one single translation for each sentence. This will be your input document file, and your goal will be to provide (automatically, through IAN) the UNL graphs for each sentence
    2. Save the translated texts (without the English original) in a plain text (.txt) file with UTF-8 encoding and upload it to UNLWEB>UNLDEV>IAN>NL FILES.
  2. Dictionary
    1. Localize the dictionary available at eng_ana_dic.txt. Note that "localization" is not the same as "translation". You may need other features (in English, for instance, nouns do not have gender or case) or other entries. In any case, the resulting dictionary should fit your translated version of the corpus (i.e., all the entries appearing in your translated version of the corpus should appear in the dictionary). For further information on localization, see Localization. For information on the dictionary structure, see Dictionary Specs. For an explanation of the structure of the English dictionary, see English Dictionary. In case you need additional features, use only the tags available at the tagset.
    2. Save the NL-UNL dictionary in a plain text (.txt) file with UTF-8 encoding and upload it to UNLWEB>UNLDEV>IAN>DICTIONARIES.
  3. Grammar
    1. Create the NL-UNL (analysis) transformation grammar necessary to analyze, in UNL, the natural language sentences of the translated corpus. This grammar is the most difficult (and the actual goal) of the whole analysis task. In order to prepare the grammar, study the Grammar Specs. Next, take a look at the structure of the English Grammar for a detailed example. In many cases, it would be simpler just to localize the English grammar to your own locale rather than creating a whole grammar from the scratch. See the instructions at Localization. The grammar is normally developed inside IAN, because we have to test it every time. But you may also prepare a draft grammar, save it in a plain text (.txt) file with UTF-8 encoding and upload it to UNLWEB>UNLDEV>IAN>T-RULES.
    2. Create the NL-UNL (analysis) disambiguation grammar in order to improve the results of the transformation and to control the process of tokenization. Again, this grammar is normally developed inside IAN (at the D-RULES tab), because we have to test it every time. Consult the English Grammar for a detailed example of a disambiguation grammar.
    3. Test the grammar against the corpus and provide the necessary changes.

NLization

  1. Corpus
    1. Upload the file corpusA1_unl.txt to UNLWEB>UNLDEV>EUGENE>UNL DOCUMENT. Do not do any change to this file.
  2. Dictionary
    1. Localize the dictionary available at eng_gen_dic.txt to your locale. Note, once again, that localization is not the same as translation. The localized version must reflect the word list of your translated corpus. In any case, use only the tags available at the tagset. For further information on the dictionary structure, see Dictionary Specs.
    2. Save the UNL-NL dictionary in a plain text (.txt) file with UTF-8 encoding and upload it to UNLWEB>UNLDEV>PROJECTS>EUGENE>DICTIONARIES.
  3. Grammar
    1. Export the inflectional grammar of your language from UNLARIUM>GRAMMAR>[YOUR LOCALE]>EXPORT. If the grammar of your language is not available yet, you may:
      1. Provide it through the UNLarium; or
      2. Create the inflectional paradigms only for the inflected forms appearing in the UNL-NL dictionary. In that case, follow the model available at English Inflectional Grammar. The documentation of the English grammar is available at English Inflectional Grammar (only for reference). For further information, see Inflectional paradigms.
    2. Save the inflectional grammar in a plain text (.txt) file with UTF-8 encoding and upload it to UNLWEB>UNLDEV>PROJECTS>EUGENE>RULES.
    3. Provide the UNL-NL (generation) T-grammar and D-grammar necessary to generate natural language sentences from the UNL corpus. Follow the sample instructions available for the analysis grammar.

Samples and Examples

The following resources have been used to deal with CorpusA1 in English and may be used as a sample of what is expected to be provided

Recommended Readings

Before starting the activity, and in order to fully understand what is expected to be done, it is important for you to be acquainted with the following documentation:

  • Tagset, because you are expected to use only the tags included in the tagset
  • UNL Dictionary Specs, which is essential to understand the dictionary structure
  • UNL Grammar Specs, which is essential to understand the grammar structure

It is also interesting to make a test drive with IAN and EUGENE.

Software