International Workshop on Systems and Frameworks for Computational Morphology

Systems and Frameworks for Computational Morphology pp 72-93 | Cite as

A Universal Feature Schema for Rich Morphological Annotation and Fine-Grained Cross-Lingual Part-of-Speech Tagging

  • John Sylak-Glassman
  • Christo Kirov
  • Matt Post
  • Roger Que
  • David Yarowsky
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 537)

Abstract

Semantically detailed and typologically-informed morphological analysis that is broadly applicable cross-linguistically has the potential to improve many NLP applications, including machine translation, n-gram language models, information extraction, and co-reference resolution. In this paper, we present a universal morphological feature schema, which is a set of features that represent the finest distinctions in meaning that are expressed by inflectional morphology across languages. We first present the schema’s guiding theoretical principles, construction methodology, and contents. We then present a method of measuring cross-linguistic variability in the semantic distinctions conveyed by inflectional morphology along the multiple dimensions spanned by the schema. This method relies on representing inflected wordforms from many languages in our universal feature space, and then testing for agreement across multiple aligned translations of pivot words in a parallel corpus (the Bible). The results of this method are used to assess the effectiveness of cross-linguistic projection of a multilingual consensus of these fine-grained morphological features, both within and across language families. We find high cross-linguistic agreement for a diverse range of semantic dimensions expressed by inflectional morphology.

Keywords

Inflectional morphology Linguistic typology Universal schema Cross-linguistic projection 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • John Sylak-Glassman
    • 1
  • Christo Kirov
    • 1
  • Matt Post
    • 2
    • 3
  • Roger Que
    • 3
  • David Yarowsky
    • 3
  1. 1.Center for Language and Speech ProcessingJohns Hopkins UniversityBaltimoreUSA
  2. 2.Human Language Technology Center of ExcellenceJohns Hopkins UniversityBaltimoreUSA
  3. 3.Department of Computer ScienceJohns Hopkins UniversityBaltimoreUSA

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