MeatAnnot is a software enabling the automatic generation of ontology-based semantic annotations: starting from a textual document, it allows us to generate a structured semantic annotation, based on a domain ontology, and describing the semantic contents of this text. MeatAnnot relies on several NLP techniques (e.g. modules of GATE (General Architecture for Text Engineering), RASP (Robust Accurate Statistical Parsing) parser and a relation extraction grammar we wrote in JAPE); it extracts information from text, instantiates concepts and relationships of the reference ontology and generates RDF annotations for the document.W
MeatAnnot was applied:
on a corpus of scientific articles in biology for the MEAT project,
on a corpus of patents in the PatAnnot system of patent mining,
on the GeneRIF (Gene Reference Into Function) corpus in the framework of the Immunosearch project,
on the Neli (National Electronic Library of Infection) Web site in the framework of the SUPROD system aimed at user profile detection ,
for term extraction from design documents of Estanda and ItalDesign in the framework of the Sevenpro project.
MeatAnnot has been distributed to IRIT.