Evaluation of NER systems for the recognition of place mentions in French thematic corpora

Abstract

Ongoing initiatives promoted by cultural institutions and public administrations engage in the development of textual corpora issued from the general public. In this work, we deal with a spoken corpus of life stories and a crowd-sourced Web corpus of people's contributions related to urban planning issues in their city. Located information constitutes an essential component in these corpora. Toponyms refer to official names (e.g. Congo) which are listed in gazetteers but often to generic locations such as un endroit très beau (a beautiful place). Because of the nature of the corpora, these generic locations are inherently subjective, vague and descriptive. For enabling automated exploitation of these texts, it is crucial to properly detect such kinds of place mentions. In this sense, the present work provides a comparative study of state-of-art NER1 systems, most importantly of supervised tools such as Stanford NER, for the identification of generic locations in thematic corpora.