Section: Scientific Foundations

Computational Linguistics and Computational Logic

The scientific foundations of TALARIS's work boil down to the motto: computational linguistics meets computational logic and knowledge representation.

From computational linguistics we take the large linguistic and lexical semantics resources, the parsing and generation algorithms, and the insight that (whenever possible) statistical information should be employed to cope with ambiguity. From computational logic and knowledge representation we take the various languages and methodologies that have been developed for handling different forms of information (such as temporal information), the computational tools (such as theorem provers, model builders, model checkers, sat-solvers and planners) that have been devised for working with them, together with the insight that, whenever possible, it is better to work with inference tools that have been tuned for particular problems, and moreover that, whenever possible, it is best to devote as little computational energy to inference as possible.

This picture is somewhat idealized. For example, for many languages (and French is one of them) the large scale linguistic resources (lexicons, grammars, WordNet, FrameNet, PropBank, etc.) that exist for English are not yet available. In addition, the syntax/semantics interface often cannot be taken for granted, and existing inference tools often need to be adapted to cope with the logics that arise in natural language applications (for example, existing provers for Description Logic, though excellent, do not cope with temporal reasoning). Thus we are not simply talking about bringing together known tools, and investigating how they work once they are combined — often a great deal of research, background work and development is needed. Nonetheless, the ideal of bringing together the best tools and ideas from computational linguistics, knowledge representation and computational logic and putting them to work in coordination is the guiding line.