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Anaphora Resolution pp 209–236Cite as

Preprocessing Technology

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Abstract

Coreference is a complex phenomenon involving a variety of linguistic factors: from surface similarity to morphological agreement, specific syntactic constraints, semantics, salience and encyclopedic knowledge. It is therefore essential for any coreference resolution system to rely on a rich linguistic representation of a document to be analyzed. This chapter focuses on the preprocessing technology, taking into consideration a variety of external tools needed to create such representations, and shows how to combine them in a Preprocessing Pipeline, in order to extract mentions of entities in a given document, describing their linguistic properties.

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Notes

  1. 1.

    In all the examples in this chapter we use square brackets to indicate correct (gold) mention boundaries.

  2. 2.

    The MUC guidelines require annotation of the SLUG, DATE, NWORDS, PREAMBLE and TEXT parts of a document.

  3. 3.

    http://projects.ldc.upenn.edu/ace/

  4. 4.

    An exception is the TK-EMD module of BART [48] that uses tree kernels to identify relevant parse nodes and classify them as ±mentions.

  5. 5.

    http://www.evalita.it/2009/tasks/entity

  6. 6.

    http://chasen.org/~taku/software/yamcha/

  7. 7.

    http://www.livememories.org/

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Author information

Authors and Affiliations

  1. DISI University of Trento, Trento, Italy

    Olga Uryupina

  2. Fondazione Bruno Kessler, Trento, Italy

    Roberto Zanoli

Authors
  1. Olga Uryupina
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  2. Roberto Zanoli
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Correspondence to Olga Uryupina .

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Editors and Affiliations

  1. Trento, Italy

    Massimo Poesio

  2. Frankfurt am Main, Germany

    Roland Stuckardt

  3. Heidelberg, Germany

    Yannick Versley

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Uryupina, O., Zanoli, R. (2016). Preprocessing Technology. In: Poesio, M., Stuckardt, R., Versley, Y. (eds) Anaphora Resolution. Theory and Applications of Natural Language Processing. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-47909-4_7

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  • DOI: https://doi.org/10.1007/978-3-662-47909-4_7

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