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Die vorliegende Arbeit wurde im Rahmen des Verbundvorhabens Verbmobil vom Bundes-ministerium f ur Bildung, Wissenschaft, Forschung und Technologie (BMBF) unter dem FF orderkennzeichen 01 IV 101 R geff ordert. Die Verantwortung f ur den Inhalt dieser Arbeit liegt bei dem Autor.
Boxer is an open-domain software component for semantic analysis of text, based on Combinatory Categorial Grammar (CCG) and Discourse Representation Theory (DRT). Used together with the C&C tools, Boxer reaches more than 95% coverage on newswire texts. The semantic representations produced by Boxer, known as Discourse Representation Structures (DRSs),(More)
This paper shows how to construct semantic representations from the derivations produced by a wide-coverage CCG parser. Unlike the dependency structures returned by the parser itself , these can be used directly for semantic interpretation. We demonstrate that well-formed semantic representations can be produced for over 97% of the sentences in unseen WSJ(More)
The DIPPER architecture is a collection of software agents for prototyping spoken dialogue systems. Implemented on top of the Open Agent Architecture (OAA), it comprises agents for speech input and output, dialogue management, and further supporting agents. We define a formal syntax and semantics for the DIP-PER information state update language. The(More)
Shared Task 1 of SemEval-2014 comprised two subtasks on the same dataset of sentence pairs: recognizing textual en-tailment and determining textual similarity. We used an existing system based on formal semantics and logical inference to participate in the first subtask, reaching an accuracy of 82%, ranking in the top 5 of more than twenty participating(More)
We compare and combine two methods to approach the second textual entailment challenge (RTE-2): a shallow method based mainly on word-overlap and a method based on logical inference, using first-order theorem proving and model building techniques. We use a machine learning technique to combine features of both methods. We submitted two runs, one using only(More)
We add an interpretable semantics to the paraphrase database (PPDB). To date, the relationship between the phrase pairs in the database has been weakly defined as approximately equivalent. We show that in fact these pairs represent a variety of relations, including directed entail-ment (little girl/girl) and exclusion (no-body/someone). We automatically(More)