Summary of the paper

Title Utilizing Constituent Structure for Compound Analysis
Authors Kristín Bjarnadóttir and Jón Daðason
Abstract Compounding is extremely productive in Icelandic and multi-word compounds are common. The likelihood of finding previously unseen compounds in texts is thus very high, which makes out-of-vocabulary words a problem in the use of NLP tools. The tool de-scribed in this paper splits Icelandic compounds and shows their binary constituent structure. The probability of a constituent in an unknown (or unanalysed) compound forming a combined constituent with either of its neighbours is estimated, with the use of data on the constituent structure of over 240 thousand compounds from the Database of Modern Icelandic Inflection, and word frequencies from Íslenskur orðasjóður, a corpus of approx. 550 million words. Thus, the structure of an unknown compound is derived by com-parison with compounds with partially the same constituents and similar structure in the training data. The granularity of the split re-turned by the decompounder is important in tasks such as semantic analysis or machine translation, where a flat (non-structured) se-quence of constituents is insufficient.
Topics Statistical and Machine Learning Methods, Lexicon, Lexical Database
Full paper Utilizing Constituent Structure for Compound Analysis
Bibtex @InProceedings{BJARNADTTIR14.954,
  author = {Kristín Bjarnadóttir and Jón Daðason},
  title = {Utilizing Constituent Structure for Compound Analysis},
  booktitle = {Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)},
  year = {2014},
  month = {may},
  date = {26-31},
  address = {Reykjavik, Iceland},
  editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Thierry Declerck and Hrafn Loftsson and Bente Maegaard and Joseph Mariani and Asuncion Moreno and Jan Odijk and Stelios Piperidis},
  publisher = {European Language Resources Association (ELRA)},
  isbn = {978-2-9517408-8-4},
  language = {english}
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