Call for Papers
Research in textual Question Answering has made substantial advances in
the past few years. The state-of-the art in answering textual
questions is beyond keyword matching. Processing of complex questions
requires multiple forms of inference, e.g. abductions, default
reasoning, inference with epistemic logic or description
logic. Additionally, there are also forms of inference that are
typical to language interpretation, e.g. conversational implicatures,
processing of metonymies and metaphors. Often, the answer to questions
involves temporal and spatial reasoning.
The challenge addressed by this workshop is posed by the
identification, discussion and comparison of different inference
mechanisms that operate on knowledge structures automatically derived
from questions or candidate answers. Unlike inference schemes devised
for manually-crafted knowledge, inference methods for Question
Answering need to be robust, cover all ambiguities of language and
operate on pragmatic information extracted from textual data. An
important component of the workshop will be the discussion of available
knowledge sources that can be used for inference of textual
answers. This workshop constitutes an occasion of bringing together
researchers from the Knowledge Representation and Reasoning (KRR)
community with researchers that work in Natural Language Processing (NLP).
Organizing Committee
Sanda Harabagiu (University of Texas at Dallas)
Dan Moldovan (University of Texas at Dallas)
Srini Narayanan (ICSI Berkeley)
Christopher Manning (Stanford University)
Daniel Bobrow (PARC)
Ken Forbus (Northwestern University)
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