We present parsing algorithms for various mildly non-projective dependency formalisms. In particular, algorithms are presented for: all well-nested structures of gap degree at mos...
We present a new approach for mapping natural language sentences to their formal meaning representations using stringkernel-based classifiers. Our system learns these classifiers ...
Several NLP tasks are characterized by asymmetric data where one class label NONE, signifying the absence of any structure (named entity, coreference, relation, etc.) dominates al...
This paper proposes a novel method of building polarity-tagged corpus from HTML documents. The characteristics of this method is that it is fully automatic and can be applied to a...
This paper proposes a generic mathematical formalism for the combination of various structures: strings, trees, dags, graphs and products of them. The polarization of the objects ...
This paper explores techniques for reducing the effectiveness of standard authorship attribution techniques so that an author A can preserve anonymity for a particular document D....
This paper describes the development of QuestionBank, a corpus of 4000 parseannotated questions for (i) use in training parsers employed in QA, and (ii) evaluation of question par...
We present a FrameNet-based semantic role labeling system for Swedish text. As training data for the system, we used an annotated corpus that we produced by transferring FrameNet ...
We propose an unsupervised segmentation method based on an assumption about language data: that the increasing point of entropy of successive characters is the location of a word ...
In this paper, we exploit non-local features as an estimate of long-distance dependencies to improve performance on the statistical spoken language understanding (SLU) problem. Th...