by Lenhart K. Schubert
Natural Language Processing and Knowledge Representation: Language for Knowledge and Knowledge for Language
http://www.cs.rochester.edu/u/schubert/papers/el-meets-lrrh.ps
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Abstract:
Abstract. We describe a comprehensive framework for narrative understanding based on Episodic Logic (EL). This situational logic was developed and implemented as a semantic representation and commonsense knowledge representation that would serve the full range of interpretive and inferential needs of general NLU. The most distinctive feature of EL is its natural language-like expressiveness. It allows for generalized quantiers, lambda abstraction, sentence and predicate modiers, sentence and predicate reication, intensional predicates (corresponding to wanting, believing, making, etc.), unreliable generalizations, and perhaps most importantly, explicit situational variables (denoting episodes, events, states of aairs, etc.) linked to arbitrary formulas that describe them. These allow episodes to be explicitly related in terms of part-whole, temporal and causal relations. Episodic logical form is easily computed from surface syntax and lends itself to eective inference. The Centrality of Representation in NLP Language understanding is an organic phenomenon, and the various stages or facets of the language understanding process | parsing, computing a representation, making inferences, etc. | should not be considered in isolation from each other. For instance, both during the computation of utterance meaning and upon its completion, a great deal of \spontaneous, " input-driven inferencing is presumed to occur, working out plausible interpretations and consequences based on the discourse interpreted so far, and on meaning postulates
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