CricketLinking: Linking Event Mentions from Cricket Match Reports to Ball Entities in Commentaries

The 2011 Cricket World Cup final match was watched by around 135 million people. Such a huge viewership demands a great experience for users of online cricket portals. Many portals like espncricinfo.com host a variety of content related to recent matches including match reports and ball-by-ball commentaries. When reading a match report, reader experience can be significantly improved by augmenting (on demand) the event mentions in the report with detailed commentaries. We build an event linking system \emph{CricketLinking} which first identifies event mentions from the reports and then links them to a set of balls. Finding linkable mentions is challenging because unlike entity linking problem settings, we do not have a concrete set of event entities to link to. Further, depending on the event type, event mentions could be linked to a single ball, or to a set of balls. Hence, identifying mention type as well as linking becomes challenging. We use a large number of domain specific features to learn classifiers for mention and mention type detection. Further, we leverage structured match, context similarity and sequential proximity to perform accurate linking. Finally, context based summarization is performed to provide a concise briefing of linked balls to each mention.