Temporal Expression Recognition in Hindi

  • Nitin Ramrakhiyani
  • Prasenjit Majumder
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8284)


Temporal annotation of plain text is considered as a useful component of modern information retrieval tasks. In this work, two approaches for identification and classification of temporal entities in Hindi are developed and analyzed. Firstly, a rule based approach is developed, which takes plain text as input and based on a set of hand-crafted rules, produces a tagged output with identified temporal expressions. This approach is shown to have a strict F1-measure of 0.83. In the other approach, a CRF based classifier is trained with human tagged data and is then tested on a test dataset. The trained classifier identifies the temporal expressions from plain text and further classifies them to various classes. This approach is shown to have a strict F1-measure of 0.78. In this process a reusable gold standard dataset for temporal tagging in Hindi was developed. Named the ILTIMEX2012 corpus, it consists of 300 manually tagged Hindi news documents.


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Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  • Nitin Ramrakhiyani
    • 1
  • Prasenjit Majumder
    • 2
  1. 1.Tata Research Development and Design CentrePuneIndia
  2. 2.DAIICTGandhinagarIndia

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