A new comprehensive framework for narrative understanding has been developed. Its centerpiece is a new situational logic calledEpisodic Logic, a knowledge and semantic representation well-adapted to the interpretive and inferential needs of general NLU. The most distinctive features of EL is its natural language-like expressiveness. It allows for generalized quantifiers, lambda abstraction, sentence and predicate modifiers, sentence and predicate reification, intensional predicates, unreliable generalizations, and perhaps most importantly, explicit situational variables 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 effective inference. (shrink)

Computational models of relevance in case-based legal reasoning have traditionallybeen based on algorithms for comparing the facts and substantive legal issues of aprior case to those of a new case. In this paper we argue that robust models ofcase-based legal reasoning must also consider the broader social and jurisprudentialcontext in which legal precedents are decided. We analyze three aspects of legalcontext: the teleological relations that connect legal precedents to the socialvalues and policies they serve, the temporal relations between prior andsubsequent (...) cases in a legal domain, and the procedural posture of legal cases,which defines the scope of their precedential relevance. Using real examples drawnfrom appellate courts of New York and Massachusetts, we show with the courts' ownarguments that the doctrine of stare decisis (i.e., similar facts should lead to similar results) is subject to contextual constraints and influences. For each of the three aspects of legal context, we outline an expanded computational framework for case-based legal reasoning that encompasses the reasoning of the examples, and provides a foundation for generating a more robust set of legal arguments. (shrink)

Many theories of explanation evaluation are based on context‐independent criteria. Such theories either restrict their consideration to explanation towards a fixed goal, or assume that all valid explanations are equivalent, so that evaluation criteria can be neutral to the goals underlying the attempt to explain. However, explanation can serve a range of purposes that place widely divergent requirements on the information an explanation must provide. It is argued that understanding what determines explanations' goodness requires a dynamic theory of evaluation, based (...) on analysis of the information needed to satisfy the many goals that can prompt explanation; this view conforms to the commonsense idea that people accept and apply explanations precisely if those explanations give the information they need. A range of goals that can underly explanation is examined, and a theory is presented for evaluating whether an explanation provides the information an explainer needs for these goals. The theory is illustrated by sketching its implementation in the computer program, ACCEPTER, which does goal‐based evaluation of the goodness of explanations for surprising events in news stories. (shrink)