Section: Research Program

Shallow processing

Participants : Éric Villemonte de La Clergerie, Benoît Sagot, Rosa Stern.

The constitution of resources such as lexica or grammars raises the issues of the evaluation of these resources to assess their quality and coverage. For this reason, Alpage was the leader of the PASSAGE ANR project (ended in June 2010), which is the follow-up of the EASy parsing evaluation campaign held in 2004 and conducted by team LIR at LIMSI.

However, although developing parsing techniques, grammars (symbolic or probabilistic), and lexica constitute the key efforts towards deep large-scale linguistic processing, these components need to be included inside a full and robust processing chain, able to handle any text from any source. The development of such linguistic chains, such as Sx Pipe , is not a trivial task [6] . Moreover, when used as a preliminary step before parsers, the quality of parsers' results strongly depends on the quality of such chains. In that regard, less-standard pre-processings such as word clustering have led to promising results [93] .

In fact, such processing chains are mostly used as such, and not only as pre-processing tools before parsing. They aim at performing the basic tasks that produce immediately usable results for many applications, such as tokenization, sentence segmentation, spelling correction, and, most importantly, named entity detection, disambiguation and resolution.