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THE ACL RD-TEC 2.0: A dataset for evaluation of term and entity recognition in computational linguistics

#What this repository contains?

The dataset is organised in the following directories:

  • `readme.txt': this file.
  • `/documents': contains the annotation guidelines as well as a paper that describe the annotation process.
  • `/annotations_during_guideline_dev': Materials related to the development of guidelines; this includes the annotated files during this process as well as the guidelines used by the annotators.
  • `/annoitation_files': contains all annotated files; these files are grouped per annotator; for ease of use, those annotations that are annotated by by both annotators are collected and again presented in the directory double_annotated_files.
  • `/pos_tagged_vertical_files': Annotation files converted to the familiar vertical format (i.e., a token or annotation tag per line). These files contain automatically obtained part-of-speech tagged and lemmas using the Stanford CoreNLP library.
  • `/raw_abstract_txt': Contains abstract text files, segmented and corrected for OCR errors. These files do not contain any annotation.
  • `/licenses': license files.


ACL RD-TEC 2.0 is developed by Dr. Anne-Kathrin Schumann and Behrang QasemiZadeh. The dataset is developed as the second version of ACL RD-TEC in order to provide annotation of terms in context.

#Other links and related materials

#Contact us If you have questions, or you would like to change or contribute to this resource, please contact Anne-Kathrin Schumann (ak47schumann at ) or Behrang QasemiZadeh (zadeh at


Behrang QasemiZadeh and Anne-Kathrin Schumann. "The ACL RD-TEC 2.0: A Language Resource for Evaluating Term Extraction and Entity Recognition Methods." In Proceedings of LREC, 2016.

Schumann, A.-K. and QasemiZadeh, B., (2015a). The ACL RD-TEC Annotation Guidelines. Saarland University and National University of Ireland, ver. 2.6 edition. Available from

QasemiZadeh, Behrang and Schumann, Anne-Kathrin, 2016, The ACL RD-TEC 2.0, LINDAT/CLARIN digital library at Institute of Formal and Applied Linguistics, Charles University in Prague,

#Useful Links:

Last edited by BQ, 08.03.2016


The ACL RD-TEC 2.0: A corpus of annotated terms in context from domain of computational linguistics






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