Large-scale Knowledge Representation Resources for Cognitive Science Research

Large-scale Knowledge Representation Resources for Cognitive Science Research Martha S. Palmer Department of Computer and Information Science, University of Pennsylvania 3330 Walnut Street, Philadelphia, PA 19104-6389 USA George A. Miller Department of Psychology, Princeton University 1-S-5 Green Hall, Princeton, NJ 08544 USA Charles J. Fillmore International Computer Science Institute, University of California at Berkeley 1947 Center St., Suite 600, Berkeley, CA 94704-1198 USA Doug Lenat Cycorp, Inc. Suite 100, 3721 Executive Center Drive, Austin, TX 78731 USA Pat Hayes Institute for Human and Machine Cognition 40 South Alcaniz Street, Pensacola, FL 32502 Treebank syntactic structures: The Proposition Bank, or PropBank. PropBank consists of argument labels for the semantic roles of individual verbs and similar predicating expressions such as participial modifiers and nominalizations. This talk will describe the PropBank verb semantic role annotation being done at Penn for both English and Chinese. The annotation process will be discussed as well as the use of existing lexical resources such as WordNet, Levin classes and VerbNet. Comparisons with similar projects, including the FrameNet Project at Berkeley and the Prague Tectogrammatics project, will be made. Motivation One of the unique features of cognitive science has been its emphasis on understanding how people represent and use knowledge. Unfortunately, knowledge representation can be quite difficult if one is starting from scratch. Having “off the shelf” representation systems that can be used for investigations can make new types of cognitive modeling efforts possible, at a scale that would otherwise be impossible. The participants in this symposium each represent a different approach to building such representational resources. George A. Miller: WordNet is a lexical database that contains 146,900 English nouns, verbs, adjectives, and adverbs that are now organized by semantic relations into 117,500 meanings, where a meaning is represented by a set of synonyms (a synset) that can be used to express that meaning. An entry in WordNet consists of a synset, a definitional gloss, and (sometimes) one or more sentences illustrating usage. The semantic relations used to organize words and entries are synonymy and antonymy, hyponymy, troponymy and hypernymy, meronymy and holonymy. A currently active project, the disambiguation of definitional glosses, will be discussed. Doug Lenat: Cognitive Science research could benefit from large-scale representational building blocks. One such building block is a broad ontology of, well, everything. Another one, resting on that, is a formal axiomatization of most of the meaning of most of those concepts; i.e., millions of axioms about those hundreds of thousands of terms. These two pieces have been worked on for twenty years -- and the better part of a person-century of effort -- as Cyc. It's been highly proprietary so far, with a small tip of its ontology exposed as OpenCyc. Starting this summer, though, Cyc is being made available in its entirety for R&D purposes for free, courtesy of Ron Brachman at DARPA's IPTO. In this presentation I will briefly describe this ResearchCyc ontology and KB, and some initial utilities provided with it (inference engine, English-Cyc lexicon, interfaces), how this might fit in with the other infrastructure elements being described in this panel, and how these might leverage your work. Charles J. Fillmore: The FrameNet project is morphing from a lexicon-building project to a system capable of providing a layer or two of semantic annotation for full sentences. My remarks will summarize the kinds of information the FrameNet database can provide now, and what it should be able to offer in the not too distant future, for researchers in language engineering and cognitive science. FrameNet is moving toward greater coverage of the lexicon, adaptation to specialist vocabularies, more systematic treatment of multiword expressions, and provisions for incorporating a wide variety of (non-core) grammatical constructions. Pat Hayes Pat Hayes, the discussant for this symposium, has the unique distinction of having inventing two of the most widely-used representations for change, the situation calculus (with John McCarthy) and histories. He is a Fellow of the American Association for Artificial Intelligence and the Cognitive Science Society. Martha S. Palmer: Recently, a consensus has been achieved as to a task-oriented level of semantic representation to be layered on top of the existing Penn