Unsupervised Open Relation Extraction

  • Hady ElsaharEmail author
  • Elena Demidova
  • Simon Gottschalk
  • Christophe Gravier
  • Frederique Laforest
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10577)


We explore methods to extract relations between named entities from free text in an unsupervised setting. In addition to standard feature extraction, we develop a novel method to re-weight word embeddings. We alleviate the problem of features sparsity using an individual feature reduction. Our approach exhibits a significant improvement by \(5.8\%\) over the state-of-the-art relation clustering scoring a F1-score of 0.416 on the NYT-FB dataset.


Relation extraction Word embedding NLP 



This work was partially funded by H2020-MSCA-ITN-2014 WDAqua (64279), ALEXANDRIA (ERC 339233) and Data4UrbanMobility (BMBF).


  1. 1.
    Augenstein, I., Maynard, D., Ciravegna, F.: Distantly supervised web relation extraction for knowledge base population. Semant. Web 7(4), 335–349 (2016)CrossRefGoogle Scholar
  2. 2.
    Jolliffe, I.T.: Principal component analysis. In: Lovric, M. (ed.) International Encyclopedia of Statistical Science, pp. 1094–1096. Springer, Heidelberg (2011). doi: 10.1007/978-3-642-04898-2_455CrossRefGoogle Scholar
  3. 3.
    Marcheggiani, D., Titov, I.: Discrete-state variational autoencoders for joint discovery and factorization of relations. Trans. ACL 4, 231–244 (2016)Google Scholar
  4. 4.
    Mintz, M., Bills, S., Snow, R., Jurafsky, D.: Distant supervision for relation extraction without labeled data. In: Proceedings of ACL 2009, pp. 1003–1011 (2009)Google Scholar
  5. 5.
    Rei, M., Cummins, R.: Sentence similarity measures for fine-grained estimation of topical relevance in learner essays. In: Proceedings of the BEA Workshop (2016)Google Scholar
  6. 6.
    Ward Jr., J.H.: Hierarchical grouping to optimize an objective function. J. Am. Statist. Assoc. 58(301), 236–244 (1963)MathSciNetCrossRefGoogle Scholar
  7. 7.
    Yao, L., Haghighi, A., Riedel, S., McCallum, A.: Structured relation discovery using generative models. In: Proceedings of EMNLP 2011 (2011)Google Scholar
  8. 8.
    Yao, L., Riedel, S., McCallum, A.: Unsupervised relation discovery with sense disambiguation. In: Proceedings of ACL 2012 (2012)Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Hady Elsahar
    • 1
    Email author
  • Elena Demidova
    • 2
  • Simon Gottschalk
    • 2
  • Christophe Gravier
    • 1
  • Frederique Laforest
    • 1
  1. 1.Univ Lyon, UJM-Saint-Etienne, CNRS, Laboratoire Hubert CurienLyonFrance
  2. 2.L3S Research CenterLeibniz Universität HannoverHannoverGermany

Personalised recommendations