Abstract
This paper explains the overview of the shared task on “Detecting Paraphrases in Indian Languages” (DPIL) conducted at FIRE 2016. Given a pair of sentences in the same language, participants were asked to detect the semantic equivalence between sentences. This shared task was proposed for four Indian languages, namely Tamil, Malayalam, Hindi, and Punjabi. There were two subtasks given under the shared task on Detecting Paraphrase in Indian Languages. Given a pair of sentences, the subtask-1 was to classify them as paraphrases or not paraphrases. The subtask-2 was to identify whether they are paraphrases or semi-paraphrases or not paraphrases. The dataset created for the shared task has been made available online, and it is the first open-source paraphrase detection corpora for Indian languages. In this overview paper, we describe both subtasks, datasets, evaluation methods and system descriptions as well as performances of the submitted runs.
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It does not affect the result of the participating teams
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Acknowledgement
First, we would like to thank FIRE 2016 organizers for giving us an opportunity to organize the shared task on Detecting Paraphrases for Indian Languages (DPIL). We would like to extend our gratitude to the advisory committee members Prof. Ramanan, RelAgent Pvt. Ltd and Prof. Rajendran S, Computational Engineering and Networking (CEN) for actively supporting us throughout the track. We would like to thank our PG students at CEN for helping us in creating the paraphrase corpora.
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Anand Kumar, M., Singh, S., Kavirajan, B., Soman, K.P. (2018). Shared Task on Detecting Paraphrases in Indian Languages (DPIL): An Overview. In: Majumder, P., Mitra, M., Mehta, P., Sankhavara, J. (eds) Text Processing. FIRE 2016. Lecture Notes in Computer Science(), vol 10478. Springer, Cham. https://doi.org/10.1007/978-3-319-73606-8_10
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DOI: https://doi.org/10.1007/978-3-319-73606-8_10
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