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Harmonization and Development of Resources and Tools for Italian Natural Language Processing within the PARLI Project pp 71–89Cite as

Comparing Named Entity Recognition on Transcriptions and Written Texts

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 589))

Abstract

The ability to recognize named entities (e.g., person, location and organization names) in texts has been proved as an important task for several natural language processing areas, including Information Retrieval and Information Extraction. However, despite the efforts and the achievements obtained in Named Entity Recognition from written texts, the problem of recognizing named entities from automatic transcriptions of spoken documents is still far from being solved. In fact, the output of Automatic Speech Recognition (ASR) often contains transcription errors; in addition, many named entities are out-of-vocabulary words, which makes them not available to the ASR. This paper presents a comparative analysis of extracting named entities both from written texts and from transcriptions. As for transcriptions, we have used spoken broadcast news, while for written texts we have used both newspapers of the same domain of the transcriptions and the manual transcriptions of the broadcast news. The comparison was carried on a number of experiments using the best Named Entity Recognition system presented at Evalita 2007.

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Notes

  1. 1.

    http://www.evalita.it/.

  2. 2.

    http://textpro.fbk.eu/.

  3. 3.

    http://gate.ac.uk/.

  4. 4.

    http://opennlp.apache.org/.

  5. 5.

    http://www.itl.nist.gov/iad/mig/tests/bnr/1998/.

  6. 6.

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

  7. 7.

    http://www.clips.ua.ac.be/conll2002/ner/bin/conlleval.txt.

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Author information

Authors and Affiliations

  1. FBK-irst, via Sommarive 18, 38123, Povo (TN), Italy

    Bernardo Magnini & Roberto Zanoli

  2. SIS Lab, Department of Information Engineering and Computer Science, University of Trento, 38123, Povo (TN), Italy

    Firoj Alam

Authors
  1. Firoj Alam
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  2. Bernardo Magnini
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  3. Roberto Zanoli
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Correspondence to Firoj Alam .

Editor information

Editors and Affiliations

  1. Department of Computer Science, Systems and Production, University of Rome Tor Vergata, Rome, Italy

    Roberto Basili

  2. Department of Computer Science, University of Turin, Turin, Italy

    Cristina Bosco

  3. Department of Language and Cultural Studies, Department of Computer Science, Ca’ Foscari University of Venice, Venezia, Italy

    Rodolfo Delmonte

  4. Department of Computer Science and Information Engineering, University of Trento, Trento, Italy

    Alessandro Moschitti

  5. Department of Computer Science, University of Pisa, Pisa, Italy

    Maria Simi

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Alam, F., Magnini, B., Zanoli, R. (2015). Comparing Named Entity Recognition on Transcriptions and Written Texts. In: Basili, R., Bosco, C., Delmonte, R., Moschitti, A., Simi, M. (eds) Harmonization and Development of Resources and Tools for Italian Natural Language Processing within the PARLI Project. Studies in Computational Intelligence, vol 589. Springer, Cham. https://doi.org/10.1007/978-3-319-14206-7_4

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  • DOI: https://doi.org/10.1007/978-3-319-14206-7_4

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  • Online ISBN: 978-3-319-14206-7

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