This paper presents a minimalist program for RDF, by showing how one can do without several predicates and keywords of the RDF Schema vocabulary, obtaining a simpler language which preserves the original semantics. This approach is beneficial in at least two directions: (a) To have a simple abstract fragment of RDFS easy to formalize and to reason about, which captures the essence of RDFS; (b) To obtain algorithmic properties of deduction and optimizations that are relevant for particular fragments. Among our results are: the identification of a simple fragment of RDFS; the proof that it encompasses the main features of RDFS; a formal semantics and a deductive system for it; sound and complete deductive systems for their sub-fragments; and an ${\cal O}(n \log n)$ complexity bound for ground entailment in this fragment.

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Minimal Deductive Systems for RDF

Beeldmateriaal speelt een steeds grotere rol in onze cultuur, maar ook in de wetenschap en in het onderwijs. Zoeken in grote collecties beeldmateriaal blijft echter een moeizaam proces. Het kost een eindgebruiker veel tijd en moeite om juist dat ene beeld te vinden. Daarom zijn er efficiente zoekmethoden nodig om de groeiende collecties doorzoekbaar te maken en te houden. Laura Hollink onderzoekt de problemen bij het zoeken naar beeldmateriaal en de mogelijke oplossingen daarvoor, in drie uiteenlopende collecties: schilderijen, foto’s van organische cellen en nieuwsuitzendingen.

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Semantic annotation for retrieval of visual resources

In this chapter we give a brief synopsis of the history of the Web, starting with Licklider through Engelbart to Berners-Lee. We then procede to dissect the various components of the World Wide Web in order to get an overview of Web architecture. The Web is distinguished from the Internet as a “universal information space” where all items of interest are named by URIs, while the Internet is a transport protocol for the transfer of bytes. Beginning with protocols to communicate between clients and servers, we explore twin notions behind information, namely encoding and content. Then, moving to the Web of URIs and web-pages, we arrive at a tentative theory of representations. Finally, we deduce from our exploration of Web architecture a number of informal principles.

Architecture of the World Wide Web

Semantic web applications leveraging NLP can benefit from easy access to expressive lexical resources such as FrameNet. However, the usefulness of FrameNet is affected by its limited coverage and non-standard semantics. The access to existing linguistic resources is also limited because of poor connectivity among them. We present some strategies based on Linguistic Linked Data to broaden FrameNet coverage and formal linkage of lexical and factual resources. We created a novel resource, Framester, which acts as a hub between FrameNet, WordNet, VerbNet, BabelNet, DBpedia, Yago, DOLCE-Zero, as well as other resources. Framester is not only a strongly connected knowledge graph, but also applies a rigorous formal treatment for Fillmore's frame semantics, enabling full-fledged OWL querying and reasoning on a large frame-based knowledge graph. We also describe Word Frame Disambiguation, an application that reuses Framester data as a base in order to perform frame detection from text, with results comparable in precision to the state of the art, but with a much higher coverage.

Framester: A Wide Coverage Linguistic Linked Data Hub

FrameNet is an important lexical knowledge base featuring cognitive plausibility, and grounded in a large corpus. Besides being actively used by the NLP community, frames are a great source of knowledge patterns once converted into a knowledge representation language. In this paper we present our experience in converting the 1.5 XML version of FrameNet into RDF datasets published on the Linked Open Data cloud, which are interoperable with WordNet and other resources. In the conversion we have used Semion, a new tool that allows a rule-based, customized pipeline from XML to RDF and OWL data. In addition, we introduce a method to select and refactor part of the information related to frames as full-fledged OWL knowledge patterns. This last result has required non-trivial assumptions on how to interpret FrameNet relations as formal knowledge.

M.F.J. van Assem

Papers

RDF/OWL Representation of WordNet