Discovering Hypernymy Relations using Text Layout

Proceedings of the Fourth Joint Conference on Lexical and Computational Semantics (*SEM 2015), pages 249–258, Denver, Colorado, June 4–5, 2015. Discovering Hypernymy Relations using Text Layout Jean-Philippe Fauconnier Institut de Recherche en Informatique de Toulouse 118, Route de Narbonne 31062 Toulouse, France faucon@irit.fr Mouna Kamel Institut de Recherche en Informatique de Toulouse 118, Route de Narbonne 31062 Toulouse, France kamel@irit.fr Abstract Hypernymy relation acquisition has been widely investigated, especially because tax- onomies, which often constitute the backbone structure of semantic resources are structured using this type of relations. Although lots of approaches have been dedicated to this task, most of them analyze only the written text. However relations between not necessar- ily contiguous textual units can be expressed, thanks to typographical or dispositional mark- ers. Such relations, which are out of reach of standard NLP tools, have been investigated in well specified layout contexts. Our aim is to improve the relation extraction task consid- ering both the plain text and the layout. We are proposing here a method which combines layout, discourse and terminological analyses, and performs a structured prediction. We fo- cused on textual structures which correspond to a well defined discourse structure and which often bear hypernymy relations. This type of structure encompasses titles and sub-titles, or enumerative structures. The results achieve a precision of about 60%. 1 Introduction The hypernymy relation acquisition task is a widely studied problem, especially because taxonomies, which often constitute the backbone structure of semantic resources like ontologies, are structured using this type of relations. Although this task has been addressed in literature, most of the publications report analyses based on the written text only, usually at the phrase or sentence level. However, a written text is not merely a set of words or sentences. When producing a document, a writer may use various layout means, in addition to strictly linguistics devices such as syntactic arrangement or rhetorical forms. Relations between textual units that are not necessarily contiguous can thus be expressed thanks to typographical or dispositional markers. Such relations, which are out of reach of standard NLP tools, have been studied within some specific layout contexts. Our aim is to improve the relation extraction task by considering both the plain text and the layout. This means (1) identifying hierarchical structures within the text using only layout, (2) identifying relations carried by these structures, using both lexico-syntactic and layout features. Such an approach is deemed novel for at least two reasons. It combines layout, discourse and terminological analyses to bridge the gap be- tween the document layout and lexical resources. Moreover, it makes a structured prediction of the whole hierarchical structure according to the set of visual and discourse properties, rather than making decisions only based on parts of this structure, as usually performed. The main strength of our approach is its ap- plicability to different document formats as well to several domains. It should be highlighted that encyclopedic, technical or scientific documents, which are often analyzed for building semantic resources, are most …

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