AI

The SMAPH System for Query Entity Recognition and Disambiguation

Abstract

The SMAPH system implements a pipeline of four main steps: (1) Fetching – it fetches the search results returned by a search engine given the query to be annotated; (2) Spotting – search result snippets are parsed to identify candidate mentions for the entities to be annotated. This is done in a novel way by detecting the keywords-in-context by looking at the bold parts of the search snippets; (3) Candidate generation – candidate entities are generated in two ways: from the Wikipedia pages occurring in the search results, and from an existing annotator, using the mentions identified in the spotting step as input; (4) Pruning – a binary SVM classifier is used to decide which entities to keep/discard in order to generate the final annotation set for the query. The SMAPH system ranked third on the development set and first on the final blind test of the 2014 ERD Challenge short text track.