We describe a word alignment platform which ensures text pre-processing (tokenization, POS-tagging, lemmatization, chunking, sentence alignment) as required by an accurate word al...
Dan Tufis, Radu Ion, Alexandru Ceausu, Dan Stefane...
Unsupervised paraphrase acquisition has been an active research field in recent years, but its effective coverage and performance have rarely been evaluated. We propose a generic ...
We propose a method for compiling bilingual terminologies of multi-word terms (MWTs) for given translation pairs of seed terms. Traditional methods for bilingual terminology compi...
In the current project, we aim at developing an approach for automatically answering why-questions. We created a data collection for research, development and evaluation of a meth...
This paper quantitatively investigates in how far local context is useful to disambiguate the senses of an ambiguous word. This is done by comparing the co-occurrence frequencies ...
All questions are implicitly associated with an expected answer type. Unlike previous approaches that require a predefined set of question types, we present a method for dynamical...
Most question answering (QA) and information retrieval (IR) systems are insensitive to different users' needs and preferences, and also to the existence of multiple, complex ...
Extending a machine learning based coreference resolution system with a feature capturing automatically generated information about semantic roles improves its performance.
Metonymy recognition is generally approached with complex algorithms that rely heavily on the manual annotation of training and test data. This paper will relieve this complexity ...