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RetroC – A Corpus for Evaluating Temporal Classifiers

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Human Language Technology. Challenges for Computer Science and Linguistics (LTC 2015)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10930))

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Abstract

We present a corpus for training and evaluating systems for the dating of Polish texts. A number of baselines (using year references, knowledge of spelling reforms and birth years) are given for the temporal classification task. We also show that the problem can be viewed as a regression problem and a standard supervised learning tool (Vowpal Wabbit) can be applied. So far, the best result has been achieved with supervised learning with word tokens and character 5-g as features. In addition, error analysis of the results obtained with the best solution are presented in this paper.

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Notes

  1. 1.

    http://ebuw.uw.edu.pl.

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Authors and Affiliations

  1. Faculty of Mathematics and Computer Science, Adam Mickiewicz University in Poznań, Poznań, Poland

    Filip Graliński

  2. Institute of Linguistics, Adam Mickiewicz University in Poznań, Poznań, Poland

    Piotr Wierzchoń

Authors
  1. Filip Graliński
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  2. Piotr Wierzchoń
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Corresponding author

Correspondence to Filip Graliński .

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Editors and Affiliations

  1. Adam Mickiewicz University, Poznań, Poland

    Zygmunt Vetulani

  2. LIMSI-CNRS, Orsay Cedex, France

    Joseph Mariani

  3. Adam Mickiewicz University, Poznań, Poland

    Marek Kubis

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Graliński, F., Wierzchoń, P. (2018). RetroC – A Corpus for Evaluating Temporal Classifiers. In: Vetulani, Z., Mariani, J., Kubis, M. (eds) Human Language Technology. Challenges for Computer Science and Linguistics. LTC 2015. Lecture Notes in Computer Science(), vol 10930. Springer, Cham. https://doi.org/10.1007/978-3-319-93782-3_8

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  • DOI: https://doi.org/10.1007/978-3-319-93782-3_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-93781-6

  • Online ISBN: 978-3-319-93782-3

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