This paper describes work carried out in the European project TrendMiner which partly deals with the extraction and representation of real time information from dynamic data streams. The focus of this paper lies on the construction of an integrated ontology, TMO, the TrendMiner Ontology, that has been assembled from several independent multilingual taxonomies and ontologies which are brought together by an interface specification, expressed in OWL. Within TrendMiner, TMO serves as a common language that helps to interlink data, delivered from both symbolic and statistical components of the TrendMiner system. Very often, the extracted data is supplied as quintuples, RDF triples that are extended by two further temporal arguments, expressing the temporal extent in which an atemporal statement is true. In this paper, we will also sneak a peek on the temporal entailment rules and queries that are built into the semantic repository hosting the data and which can be used to derive useful new information.

In this paper, we report on first attempts and findings to analyzing German patient records, using a hybrid parsing architecture and a combination of two relation extraction strategies. On a practical level, we are interested in the extraction of concepts and relations among those concepts, a necessary cornerstone for building medical information systems. The parsing pipeline consists of a morphological analyzer, a robust chunk parser adapted to Latin phrases used in medical diagnosis, a repair rule stage, and a probabilistic context-free parser that respects the output from the chunker. The relation extraction stage is a combination of two systems: SProUT, a shallow processor which uses hand-written rules to discover relation instances from local text units and DARE which extracts relation instances from complete sentences, using rules that are learned in a bootstrapping process, starting with semantic seeds. Two small experiments have been carried out for the parsing pipeline and the relation extraction stage.

We present on-going work on the harmonization of existing German lexical resources in the field of opinion and sentiment mining. The input of our harmonization effort consisted in four distinct lexicons of German word forms, encoded either as lemmas or as full forms, marked up with polarity features, at distinct granularity levels. We describe how the lexical resources have been mapped onto each other, generating a unique list of entries, with unified Part-of-Speech information and basic polarity features. Future work will be dedicated to the comparison of the harmonized lexicon with German corpora annotated with polarity information. We are further aiming at both linking the harmonized German lexical resources with similar resources in other languages and publishing the resulting set of lexical data in the context of the Linguistic Linked Open Data cloud.

In the first part of this paper, we present a framework for enriching arbitrary upper or domain-specific ontologies with a concept of time. To do so, we need the notion of a time slice. Contrary to other approaches, we directly interpret the original entities as time slices in order to (i) avoid a duplication of the original ontology and (ii) to prevent a knowledge engineer from ontology rewriting. The diachronic representation of time is complemented by a sophisticated time ontology that supports underspecification and an arbitrarily fine granularity of time. As a showcase, we describe how the time ontology has been interfaced with the PROTON upper ontology. The second part investigates a temporal extension of RDF that replaces the usual triple notation by a more general tuple representation. In this setting, Hayes/ter Horst-like entailment rules are replaced by their temporal counterparts. Our motivation to move towards this direction is twofold: firstly, extending binary relation instances with time leads to a massive proliferation of useless objects (independently of the encoding); secondly, reasoning and querying with such extended relations is extremely complex, expensive, and error-prone.

Official travel warnings published regularly in the internet by the ministries for foreign affairs of France, Germany, and the UK provide a useful resource for assessing the risks associated with travelling to some countries. The shallow IE system SProUT has been extended to meet the specific needs of delivering a language-neutral output for English, French, or German input texts. A shared type hierarchy, a feature-enhanced gazetteer resource, and generic techniques of merging chunk analyses into larger results are major reusable results of this work.

We present a context-free approximation of unification-based grammars, such as HPSG or PATR-II. The theoretical underpinning is established through a least fixpoint construction over a certain monotonic function. In order to reach a finite fixpoint, the concrete implementation can be parameterized in several ways , either by specifying a finite iteration depth, by using different restrictors, or by making the symbols of the CFG more complex adding annotations a la GPSG. We also present several methods that speed up the approximation process and help to limit the size of the resulting CF grammar.

Typed feature formalisms (TFF) play an increasingly important role in NLP and, in particular, in MT. Many of these systems are inspired by Pollard and Sag’s work on Head-Driven Phrase Structure Grammar (HPSG), which has shown that a great deal of syntax and semantics can be neatly encoded within TFF. However, syntax and semantics are not the only areas in which TFF can be beneficially employed. In this paper, I will show that TFF can also be used as a means to model finite automata (FA) and to perform certain types of logical inferencing. In particular, I will (i) describe how FA can be defined and processed within TFF and (ii) propose a conservative extension to HPSG, which allows for a restricted form of semantic processing within TFF, so that the construction of syntax and semantics can be intertwined with the simplification of the logical form of an utterance. The approach which I propose provides a uniform, HPSG-oriented framework for different levels of linguistic processing, including allomorphy and morphotactics, syntax, semantics, and logical form simplification.