Event detection using trigger chain
S. Sangeetha, Ramjeevan Singh Thakur, Michael Arock · International Journal of Knowledge Engineering and Data Mining · 2012
This paper describes a new architecture for event detection from text documents. The proposed system correctly identifies the sentences that describe an event of interest, using trigger chain to extract its participants. It exploits supervised method for identifying the lexical chains from the raw sentences adopted as a training data. Lexical chain holds the set of semantically related words of a document from which it was obtained. The proposed system learns lexical chain, prepositions, and types of named entities from the training data to construct a trigger chain. It identifies events using this trigger chain. The entire architecture is divided into three tasks namely; natural language pre-processing, trigger chain construction and event identification.