Chung Hee Hwang

The TRAINS Project: A Case Study in Defining a Conversational Planning Agent

The TRAINS project is an effort to build a conversationally proficient planning assistant. A key part of the project is the construction of the TRAINS system, which provides the research platform for a wide range of issues in natural language understanding, mixed-initiative planning systems, and representing and reasoning about time, actions and events. Four years have now passed since the beginning of the project. Each year we have produced a demonstration system that focused on a dialog that illustrates particular aspects of our research. The commitment to building complete integrated systems is a significant overhead on the research, but we feel it is essential to guarantee that the results constitute real progress in the field. This paper describes the goals of the project, and our experience with the effort so far. .pp This paper is to appear in the Journal of Experimental and Theoretical AI, 1995.

TENSE TREES AS THE "FINE STRUCTURE" OF DISCOURSE

We present a new compositional tense-aspect deindexing mechanism that makes use of tense trees as components of discourse contexts. The mechanism allows reference episodes to be correctly identified even for embedded clauses and for discourse that involves shifts in temporal perspective, and permits deindexed logical forms to be automatically computed with a small number of deindexing rules.

Interpreting Tense, Aspect and Time Adverbials: A Compositional, Unified Approach

We extend our theory of English tense, aspect and time adverbials [Hwang and Schubert, 1992, 1993] to deal with a wider range of time adverbials, including many adverbials of frequency, cardinality, duration, and time span, and adverbials of temporal relation involving subordinating conjunctions such as after, since, and until. Our theory is fully formal in that it derives indexical (quasi-)logical forms from syntactic-semantic rule pairs of a formal grammar, and nonindexical logical forms via deindexing rules in the form of equivalences and equations. The grammar allows for complex sentences and the semantic rules and deindexing rules are easy to implement computationally, producing formulas in Episodic Logic.

Episodic Logic: A comprehensive, natural representation for language understanding

A new comprehensive framework for narrative understanding has been developed. Its centerpiece is a new situational logic calledEpisodic Logic (EL), 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 (corresponding to wanting, believing, making, etc.), unreliable generalizations, and perhaps most importantly, explicit situational variables (denoting episodes, events, states of affairs, 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 effective inference.

Interpreting temporal adverbials

We take for granted that sentences describe situations [2, 12]. One of the most important properties of situations are then their temporal locations, which are indicated by tense and aspect and temporal adverbials in the surface form. In [10, 22], we offered a formal theory for English tense and aspect and an algorithm that computes the temporal relationships between the situations implicitly introduced by a text. In the present paper, we propose a systematic approach to temporal adverbials, fully integrated with our tense-aspect theory and the interpretive algorithms, using the Episodic Logic (EL) formalism [9, 11, 12, 21].