Linking Entities in #Microposts
Romil Bansal, Sandeep Panem, Priya Radhakrishnan, Manish Gupta, Vasudeva Varma · 2014
Social media has emerged to be an important source of informa-tion. Entity linking in social media provides an effective way to extract useful information from microposts shared by the users. En-tity linking in microposts is a difficult task as they lack sufficient context to disambiguate the entity mentions. In this paper, we do entity linking by first identifying entity mentions and then disam-biguating the mentions based on three different features: (1) simi-larity between the mention and the corresponding Wikipedia entity pages; (2) similarity between the mention and the tweet text with the anchor text strings across multiple webpages, and (3) popularity of the entity on Twitter at the time of disambiguation. The system is tested on the manually annotated dataset provided by Named Entity Extraction and Linking (NEEL) Challenge 2014, and the obtained results are on par with the state-of-the-art methods.