Papers by Pallab Bhattacharjee
HiNER: A large Hindi Named Entity Recognition Dataset (2022.lrec-1)
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Rudra Murthy, Pallab Bhattacharjee, Rahul Sharnagat, Jyotsana Khatri, Diptesh Kanojia, Pushpak Bhattacharyya
| Challenge: | Named Entity Recognition (NER) is a lowerlevel task that aims to provide class labels like Person, Location, Organisation, Time, and Number to words in free text. |
| Approach: | They propose to use a standard-abiding Hindi NER dataset to analyze the annotations of a class of naming entities in free text. |
| Outcome: | The proposed dataset achieves a weighted F1 score of 88.78 with all the tags and 92.22 when we collapse the tag-set. |