In this paper, we suggest to increase the quality and the precision of a document description using publication’s context description. Today, a lot of linguistic resources are both available on line and described by specific metadata. We first integrate them into an ontology which describes how linguists consider their primary data and tools. Then, we add to this ontology an inference system based on the information flow theory in order to establish causal relations between heterogeneous data. The result of the inference is characterized by a small set of properties which are embedded into three sequences of metadata enhancing the usual metadata describing publications.

One of the most salient subfields of AI is computational linguistics, which includes its applied branch - natural language processing (NLP). Computational linguistics is a subfield of AI, developing methods and algorithms for all the aspects of language analysis and their computer implementation. We can see language analysis split into two parts: the theoretic analysis and the applicative one. The theoretic aspect includes standard levels considered in linguistics: semantics, syntax, and morphology. Semantic theories have to be a guide of syntactical theories and morphological developments.