In this paper we describe the ongoing work on the Circumstantial Event Ontology (CEO), a newly developed ontology for calamity events that models semantic circumstantial relations between event classes. The circumstantial relations are designed manually, based on the shared properties of each event class. We discuss and contrast two types of event circumstantial relations: semantic circumstantial relations and episodic circumstantial relations. Further, we show the metamodel and the current contents of the ontology and outline the evaluation of the CEO.

We describe Open Dutch WordNet, which has been derived from the Cornetto database, the Princeton WordNet and open source resources. We exploited existing equivalence relations between Cornetto synsets and WordNet synsets in order to move the open source content from Cornetto into WordNet synsets. Currently, Open Dutch Wordnet contains 117,914 synsets, of which 51,588 synsets contain at least one Dutch synonym, which leaves 66,326 synsets still to obtain a Dutch synonym. The average polysemy is 1.5. The resource is currently delivered in XML under the CC BY-SA 4.0 license1 and it has been linked to the Global Wordnet Grid. In order to use the resource, we refer to: https: //github.com/MartenPostma/OpenDutchWordnet.

This paper presents the Event and Implied Situation Ontology (ESO), a resource which formalizes the pre and post situations of events and the roles of the entities affected by an event. The ontology reuses and maps across existing resources such as WordNet, SUMO, VerbNet, PropBank and FrameNet. We describe how ESO is injected into a new version of the Predicate Matrix and illustrate how these resources are used to detect information in large document collections that otherwise would have remained implicit. The model targets interpretations of situations rather than the semantics of verbs per se. The event is interpreted as a situation using RDF taking all event components into account. Hence, the ontology and the linked resources need to be considered from the perspective of this interpretation model.

This paper presents the Event and Implied Situation Ontology (ESO), a manually constructed resource which formalizes the pre and post situations of events and the roles of the entities affected by an event. The ontology is built on top of existing resources such as WordNet, SUMO and FrameNet. The ontology is injected to the Predicate Matrix, a resource that integrates predicate and role information from amongst others FrameNet, VerbNet, PropBank, NomBank and WordNet. We illustrate how these resources are used on large document collections to detect information that otherwise would have remained implicit. The ontology is evaluated on two aspects: recall and precision based on a manually annotated corpus and secondly, on the quality of the knowledge inferred by the situation assertions in the ontology. Evaluation results on the quality of the system show that 50% of the events typed and enriched with ESO assertions are correct.

This paper presents the general architecture of the TMEKO protocol (Tutoring Methodology for Enriching the Kyoto Ontology) that guides non-expert users through the process of creating mappings from domain wordnet synsets to a shared ontology by answering natural language questions. TMEKO will be part of a Wiki-like community platform currently developed in the Kyoto project (http://www.kyoto-project.eu). The platform provides the architecture for ontology based fact mining to enable knowledge sharing across languages and cultures. A central part of the platform is the Wikyoto editing environment in which users can create their own domain wordnet for seven different languages and define relations to the central and shared ontology based on DOLCE. A substantial part of the mappings will involve important processes and qualities associated with the concept. Therefore, the TMEKO protocol provides specific interviews for creating complex mappings that go beyond subclass and equivalence relations. The Kyoto platform and the TMEKO protocol are developed and applied to the environment domain for seven different languages (English, Dutch, Italian, Spanish, Basque, Japanese and Chinese), but can easily be extended and adapted to other languages and domains.

Cornetto is a two-year Stevin project (project number STE05039) in which a lexical semantic database is built that combines Wordnet with Framenet-like information for Dutch. The combination of the two lexical resources (the Dutch Wordnet and the Referentie Bestand Nederlands) will result in a much richer relational database that may improve natural language processing (NLP) technologies, such as word sense-disambiguation, and language-generation systems. In addition to merging the Dutch lexicons, the database is also mapped to a formal ontology to provide a more solid semantic backbone. Since the database represents different traditions and perspectives of semantic organization, a key issue in the project is the alignment of concepts across the resources. This paper discusses our methodology to first automatically align the word meanings and secondly to manually revise the most critical cases.

The goal of this paper is to describe how adjectives are encoded in Cornetto, a semantic lexical database for Dutch. Cornetto combines two existing lexical resources with different semantic organisation, i.e. Dutch Wordnet (DWN) with a synset organisation and Referentie Bestand Nederlands (RBN) with an organisation in Lexical Units. Both resources will be aligned and mapped on the formal ontology SUMO. In this paper, we will first present details of the description of adjectives in each of the the two resources. We will then address the problems that are encountered during alignment to the SUMO ontology which are greatly due to the fact that SUMO has never been tested for its adequacy with respect to adjectives. We contrasted SUMO with an existing semantic classification which resulted in a further refined and extended SUMO geared for the description of adjectives.