XML NLP Pipeline

Link:
Autor/in:
Verlag/Körperschaft:
Universität Hamburg
Erscheinungsjahr:
2021
Medientyp:
Software
Schlagworte:
  • Java
  • Dehmel Digital
  • XML
  • NLP
Beschreibung:
  • The XML NLP Pipeline is a Java command line application that integrates the Stanford CoreNLP pipeline (Manning et al. 2014) in an XML-based processing pipeline. It uses a simplified version of the Separated Markup API for XML (SMAX) by Nico Verwer (Verwer 2020) to patch the annotated tokens back to the XML document, preserving all previous annotations.

    Bibliography

    Imsieke, Gerrit. 2018. “Tokenized-to-Tree: An XProc/XSLT Library For Patching Back Tokenization/Analysis Results Into Marked-up Text.” In XML Prague 2018 Conference Proceedings, 229–45. Prague, Czech Republic.

    Manning, Christopher D., Mihai Surdeanu, John Bauer, Jenny Finkel, Steven J. Bethard, and David McClosky. 2014. “The Stanford CoreNLP Natural Language Processing Toolkit.” In Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics: System Demonstrations, 55–60. http://www.aclweb.org/anthology/P/P14/P14-5010.

    Verwer, Nico. “Plain Text Processingin Structured Documents.” In Proceedings of Declarative Amsterdam 2020. CWI, Amsterdam: John Benjamins, 2020. https://doi.org/10.1075/da.2020.verwer.plain-text-processing.

  • {"references": ["Imsieke, Gerrit. 2018. \"Tokenized-to-Tree: An XProc/XSLT Library For Patching Back Tokenization/Analysis Results Into Marked-up Text.\" In XML Prague 2018 Conference Proceedings, 229\u201345. Prague, Czech Republic.", "Manning, Christopher D., Mihai Surdeanu, John Bauer, Jenny Finkel, Steven J. Bethard, and David McClosky. 2014. \"The Stanford CoreNLP Natural Language Processing Toolkit.\" In Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics: System Demonstrations, 55\u201360.", "Verwer, Nico. \"Plain Text Processingin Structured Documents.\" In Proceedings of Declarative Amsterdam 2020. CWI, Amsterdam: John Benjamins, 2020"]}
relatedIdentifier:
DOI 10.1075/da.2020.verwer.plain-text-processing DOI 10.3115/v1/P14-5010 DOI 10.25592/uhhfdm.8964
Lizenzen:
  • https://opensource.org/licenses/GPL-3.0
  • info:eu-repo/semantics/openAccess
Quellsystem:
Forschungsdatenrepositorium der UHH

Interne Metadaten
Quelldatensatz
oai:fdr.uni-hamburg.de:9443