Summary of the paper

Title Text Mining for History: first steps on building a large dataset
Authors Suemi Higuchi, Cláudia Freitas, Bruno Cuconato and Alexandre Rademaker
Abstract This paper presents the initial efforts towards the creation of a new corpus on the history domain. Motivated by the historians' need to interrogate a vast material - almost 12 million words and more than three hundred thousand sentences - in a non-linear way, our approach privileges deep linguistic analysis on an encyclopedic-style data. In this context, the work presented here focuses on the preparation of the corpus, which is prior to the mining activity: the morphosyntactic annotation and the definition of semantic types for entities and relations relevant to the History domain. Taking advantage of the semantic nature of appositive constructions, we manually analyzed a sample of eleven hundred sentences in order to verify its potential as additional semantic clues to be considered. The results show that we are on the right track.
Topics Named Entity Recognition, Information Extraction, Information Retrieval, Corpus (Creation, Annotation, Etc.)
Full paper Text Mining for History: first steps on building a large dataset
Bibtex @InProceedings{HIGUCHI18.1084,
  author = {Suemi Higuchi and Cláudia Freitas and Bruno Cuconato and Alexandre Rademaker},
  title = "{Text Mining for History: first steps on building a large dataset}",
  booktitle = {Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)},
  year = {2018},
  month = {May 7-12, 2018},
  address = {Miyazaki, Japan},
  editor = {Nicoletta Calzolari (Conference chair) and Khalid Choukri and Christopher Cieri and Thierry Declerck and Sara Goggi and Koiti Hasida and Hitoshi Isahara and Bente Maegaard and Joseph Mariani and Hélène Mazo and Asuncion Moreno and Jan Odijk and Stelios Piperidis and Takenobu Tokunaga},
  publisher = {European Language Resources Association (ELRA)},
  isbn = {979-10-95546-00-9},
  language = {english}
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