prof. dr. J. Bos
Professor of Computational Semantics
Dutch FrameNet -- Framing Situations in the Dutch Language
(NWO Vrije Competitie 2019-2023)
Language plays a central role in framing, as we daily choose which nouns and verbs describe or frame a given situation. For some languages, researchers created databases (called FrameNets) containing rich collections of conceptual schemas (frames) that describe situations from a certain perspective. These frames are connected to words and sentences that express them. Several lexical resources exist for Dutch, but no FrameNet. Moreover, we have limited knowledge of the variation of framing in Dutch and how this compares to other languages.
Lost in Translation -- Found in Meaning
(NWO vici grant: 2015-2020)
Translating from one language into another is a complex task and meaning, undoubtly, plays a crucial role. Paradoxically, often slight changes in meaning improve translations. The aim of this project is to find out what the conditions are that determine good and bad translations, and investigate what role meaning plays in this process. The first results are presented in the Parallel Meaning Bank.
Deep Meaning Annotation Project
(endowed chair project: 2010-2015)
The D-MAP project is concerned with the development of a large-scale deep semantic annotation of text and its application of machine learning methods in computational semantics. The focus is on integration of different aspects of meaning (word senses, thematic roles, quantifier scope, tense and aspect, anaphora, presupposition, rhetorical relations, background knowledge) into one semantic formalism. The results are presented in the Groningen Meaning Bank. Players of Wordrobe help to improve the meaning bank.
Verb Phrase Ellipsis
(cross-faculty research project: 2010-2011)
Verb phrase ellipsis (VPE) has been studied in great depth in theoretical linguistics, but empirical studies of VPE are rare. We extend the few previous corpus studies with an annotated corpus of VPE in all 25 sections of the Wall Street Journal corpus (WSJ) distributed with the Penn Treebank. Our annotation is theory neutral, and has better coverage than earlier efforts that relied on automatic methods. The resulting corpus will be useful for studying VPE phenomena as well as for evaluating natural language processing systems equipped with ellipsis resolution algorithms. The stand-off annotation is freely available for research purposes.
|Last modified:||29 April 2020 10.48 a.m.|