Hybridizing formal and linguistic semantics for the Multilingual Semantic Web

1. Semantics: a serendipitous chaos The current uptake of " semantic technologies " requires an effort to design some in-teroperability for the representation practices among fields as diverse as knowledge representation and reasoning (KR), lexical semantics, information extraction, databases , (semantic) Web standards, Web 2.0 folksonomies, etc. Multilingual linguistic elements, ontologies, and semantics are key components that are shared by those fields, but are approached in heterogeneous ways. Due to the enormous amount of legacy data and representation practices, we cannot count only on standardisation efforts to build useful applications. In the forthcoming Multilingual Semantic Web (MSW), we need to live with the " serendipitous chaos " that character-ises knowledge (and linguistic) management and engineering. Too rigorous requirements are not sustainable, as the history of the Semantic Web in the last ten years suggests: logical consistency cannot always be enforced, identity of entities is often questionable, data are not always reliable and usually incomplete, knowledge can take many forms, assignment of predicates to objects can be made for unpredictable reasons, and can change dynamically, the intended meaning of predicates cannot even be studied to a full extent, because any two persons can have various levels of competences, and different needs for their interaction with their environments , often entering a dialectic or even conflicting interaction. Even more importantly , data and content are rarely structured in a cognitively sound way, or in a way that is relevant to the humans or applications that use them [1]. For those reasons, we have requirements for an agile semantics that (1) overarches the different representation practices, (2) is able to deal with incompleteness and errors , but also (3) assumes cognitive relevance by default. In everyday life, any sign that we use or perceive (the perception of a segment of the world, an image, a word, a sentence, a scientific handbook, a novel) is not typically interpreted as it is supposed to be according to an ontology, dictionary, or other quasi-normative resources, but as a function of what we can do with it, i.e. as a relevance function, also known as an affordance [2]. For MSW this is a very important assumption, because when we envisage applications that are cross-linguistic, they need to work at the level of cognitive relevance, not at that of single, decontextualized data or term equivalences. A representation language that integrates ontologies and (multi-, cross-)linguistic data needs then to …