Videos of the LREC 2022 contributions available

      Comments Off on Videos of the LREC 2022 contributions available

For the poster presentations at LREC 2022, the recorded presentations can be found below:

I still have Time(s): Extending HeidelTime for German Texts [1]

German Parliamentary Corpus (GerParCor) [2]

Total: 2

  • [PDF] [https://aclanthology.org/2022.lrec-1.505] A. Lücking, M. Stoeckel, G. Abrami, and A. Mehler, “I still have Time(s): Extending HeidelTime for German Texts,” in Proceedings of the Language Resources and Evaluation Conference, Marseille, France, 2022, pp. 4723-4728.
    [Abstract] [Poster][BibTeX]

    HeidelTime is one of the most widespread and successful tools for detecting temporal expressions in texts. Since HeidelTime’s pattern matching system is based on regular expression, it can be extended in a convenient way. We present such an extension for the German resources of HeidelTime: HeidelTimeExt. The extension has been brought about by means of observing false negatives within real world texts and various time banks. The gain in coverage is 2.7 \% or 8.5 \%, depending on the admitted degree of potential overgeneralization. We describe the development of HeidelTimeExt, its evaluation on text samples from various genres, and share some linguistic observations. HeidelTimeExt can be obtained from https://github.com/texttechnologylab/heideltime.
    @InProceedings{Luecking:Stoeckel:Abrami:Mehler:2022,
      Author         = {L\"{u}cking, Andy and Stoeckel, Manuel and Abrami, Giuseppe and Mehler, Alexander},
      title     = {I still have Time(s): Extending HeidelTime for German Texts},
      booktitle      = {Proceedings of the Language Resources and Evaluation Conference},
      month          = {June},
      year           = {2022},
      address        = {Marseille, France},
      publisher      = {European Language Resources Association},
      pages     = {4723--4728},
      abstract  = {HeidelTime is one of the most widespread and successful tools for detecting temporal expressions in texts. Since HeidelTime’s pattern matching system is based on regular expression, it can be extended in a convenient way. We present such an extension for the German resources of HeidelTime: HeidelTimeExt. The extension has been brought about by means of observing false negatives within real world texts and various time banks. The gain in coverage is 2.7 \% or 8.5 \%, depending on the admitted degree of potential overgeneralization. We describe the development of HeidelTimeExt, its evaluation on text samples from various genres, and share some linguistic observations. HeidelTimeExt can be obtained from https://github.com/texttechnologylab/heideltime.},
      url       = {https://aclanthology.org/2022.lrec-1.505}, 
      poster   = {https://www.texttechnologylab.org/wp-content/uploads/2022/06/HeidelTimeExt_LREC_2022.pdf},
      pdf    = {http://www.lrec-conf.org/proceedings/lrec2022/pdf/2022.lrec-1.505.pdf}
    }
  • [PDF] [https://aclanthology.org/2022.lrec-1.202] G. Abrami, M. Bagci, L. Hammerla, and A. Mehler, “German Parliamentary Corpus (GerParCor),” in Proceedings of the Language Resources and Evaluation Conference, Marseille, France, 2022, pp. 1900-1906.
    [Abstract] [Poster][BibTeX]

    Parliamentary debates represent a large and partly unexploited treasure trove of publicly accessible texts. In the German-speaking area, there is a certain deficit of uniformly accessible and annotated corpora covering all German-speaking parliaments at the national and federal level. To address this gap, we introduce the German Parliamentary Corpus (GerParCor). GerParCor is a genre-specific corpus of (predominantly historical) German-language parliamentary protocols from three centuries and four countries, including state and federal level data. In addition, GerParCor contains conversions of scanned protocols and, in particular, of protocols in Fraktur converted via an OCR process based on Tesseract. All protocols were preprocessed by means of the NLP pipeline of spaCy3 and automatically annotated with metadata regarding their session date. GerParCor is made available in the XMI format of the UIMA project. In this way, GerParCor can be used as a large corpus of historical texts in the field of political communication for various tasks in NLP.
    @InProceedings{Abrami:Bagci:Hammerla:Mehler:2022,
      author    = {Abrami, Giuseppe  and  Bagci, Mevlüt  and  Hammerla, Leon  and  Mehler, Alexander},
      title     = {German Parliamentary Corpus (GerParCor)},
      booktitle      = {Proceedings of the Language Resources and Evaluation Conference},
      month          = {June},
      year           = {2022},
      address        = {Marseille, France},
      publisher      = {European Language Resources Association},
      pages     = {1900--1906},
      abstract  = {Parliamentary debates represent a large and partly unexploited treasure trove of publicly accessible texts. In the German-speaking area, there is a certain deficit of uniformly accessible and annotated corpora covering all German-speaking parliaments at the national and federal level. To address this gap, we introduce the German Parliamentary Corpus (GerParCor). GerParCor is a genre-specific corpus of (predominantly historical) German-language parliamentary protocols from three centuries and four countries, including state and federal level data. In addition, GerParCor contains conversions of scanned protocols and, in particular, of protocols in Fraktur converted via an OCR process based on Tesseract. All protocols were preprocessed by means of the NLP pipeline of spaCy3 and automatically annotated with metadata regarding their session date. GerParCor is made available in the XMI format of the UIMA project. In this way, GerParCor can be used as a large corpus of historical texts in the field of political communication for various tasks in NLP.},
      url       = {https://aclanthology.org/2022.lrec-1.202},
      poster   = {https://www.texttechnologylab.org/wp-content/uploads/2022/06/GerParCor_LREC_2022.pdf},
      pdf    = {http://www.lrec-conf.org/proceedings/lrec2022/pdf/2022.lrec-1.202.pdf}
    
    }