Text mining for history: first steps on building a large dataset

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This paper presents the initial efforts towards the creation of a new corpus on the history domain. Motivated by the historians’ need to interrogate a vast material - almost 9 million words - in a non-linear way, our approach privileges deep linguistic analysis on an encyclopaedic style data. In this context, the work presented here focuses on the preparation of the corpus, which is prior to the mining activity: the morphosyntactic annotation, the definition of semantic types for named entity (NE) and named entities relations relevant to the History domain. Taking advantage of the semantic nature of appositive structures, we manually analysed a sample of 1,049 sentences in order to verify its potential as additional semantic clues to be considered. The results show that we are on the right track.

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