Abstract
The present paper describes experiments on automatically extracting typological linguistic features of natural languages from traditional written descriptive grammars. The feature-extraction task has high potential value in typological, genealogical, historical, and other related areas of linguistics that make use of databases of structural features of languages. Until now, extraction of such features from grammars has been done manually, which is highly time and labor consuming and becomes prohibitive when extended to the thousands of languages for which linguistic descriptions are available. The system we describe here starts from semantically parsed text over which a set of rules are applied in order to extract feature values. We evaluate the system’s performance on the manually curated Grambank database as the gold standard and report the first measures of precision and recall for this problem.
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Notes
- 1.
An adnominal property word corresponds to an adjective or participle in English and many other languages.
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A Tibeto-Burman language of Burma with about 10,000 speakers.
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The argument string is split into a set of words using NLTK’s word tokenizer.
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An Atlantic-Congo language spoken in Africa.
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A Chibchan language spoken in Central America.
- 7.
In a separate study we found that the average cost for a salaried student assistant to extract one datapoint from a descriptive grammar is 1.53 EUR.
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Virk, S.M., Borin, L., Saxena, A., Hammarström, H. (2017). Automatic Extraction of Typological Linguistic Features from Descriptive Grammars. In: Ekštein, K., Matoušek, V. (eds) Text, Speech, and Dialogue. TSD 2017. Lecture Notes in Computer Science(), vol 10415. Springer, Cham. https://doi.org/10.1007/978-3-319-64206-2_13
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DOI: https://doi.org/10.1007/978-3-319-64206-2_13
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