Transforming Wikipedia into Named Entity Training Data

Transforming Wikipedia into Named Entity Training Data - scientific work related to Wikipedia quality published in 2008, written by Joel Nothman, James R. Curran and Tara Murphy.

Overview

Statistical named entity recognisers require costly hand-labelled training data and, as a result, most existing corpora are small. Authors exploit Wikipedia to create a massive corpus of named entity annotated text. Authors transform Wikipedia’s links into named entity annotations by classifying the target articles into common entity types (e.g. person, organisation and location). Comparing to MUC, CONLL and BBN corpora, Wikipedia generally performs better than other cross-corpus train/test pairs.