Bill Byrne
November 24th
4:30PM
"Hierarchical Phrase-based Translation with Weighted Finite State Transducers "
Generic knowledge: acquisition and representation
Lenhart Schubert - October 06th, 2009
University of Rochester
Abstract
AI is beginning to make some dents in the "knowledge acquisition
bottleneck", the problem of acquiring large amounts of general
world knowledge to support language understanding and commonsense
reasoning. Two text-based approaches to the problem are
(1) to abstract such knowledge from patterns of predication
and modification in miscellaneous texts, and (2) to derive such
knowledge by direct interpretation of general statements in
ordinary language, such as are found in lexicons and resources
like Open Mind. I will discuss the status of our efforts in
these directions (currently centered around the KNEXT system),
and the problems that are encountered. Among these problems are
what exactly is meant by generalities such as "Cats land on their
feet", and how this meaning should be formalized. One particular
difficulty is that such statements typically involve ``donkey
anaphora". I will suggest a "dynamic Skolemization" approach
that leads naturally to script- or frame-like representations,
of the sort that have been developed in AI independently of
linguistic considerations.
Biography
Lenhart Schubert is a professor of computer science at the University
of Rochester, with primary interests in natural language understanding,
knowledge representation and acquisition, reasoning, and self-awareness.
He is a fellow of the AAAI, has served as program chair for several
AI/KR/CL conferences, and has published over a hundred articles,
including ones in philosophical and linguistic handbooks and encyclopedias.
Abstract
AI is beginning to make some dents in the "knowledge acquisition bottleneck", the problem of acquiring large amounts of general world knowledge to support language understanding and commonsense reasoning. Two text-based approaches to the problem are (1) to abstract such knowledge from patterns of predication and modification in miscellaneous texts, and (2) to derive such knowledge by direct interpretation of general statements in ordinary language, such as are found in lexicons and resources like Open Mind. I will discuss the status of our efforts in these directions (currently centered around the KNEXT system), and the problems that are encountered. Among these problems are what exactly is meant by generalities such as "Cats land on their feet", and how this meaning should be formalized. One particular difficulty is that such statements typically involve ``donkey anaphora". I will suggest a "dynamic Skolemization" approach that leads naturally to script- or frame-like representations, of the sort that have been developed in AI independently of linguistic considerations.
Biography
Lenhart Schubert is a professor of computer science at the University of Rochester, with primary interests in natural language understanding, knowledge representation and acquisition, reasoning, and self-awareness. He is a fellow of the AAAI, has served as program chair for several AI/KR/CL conferences, and has published over a hundred articles, including ones in philosophical and linguistic handbooks and encyclopedias.