Gathering Statistics to Aspectually Classify Sentences with a Genetic Algorithm

This paper presents a method for large corpus analysis to semantically classify an entire clause. In particular, we use cooccurrence statistics among similar clauses to determine the aspectual class of an input clause. The process examines linguistic features of clauses that are relevant to aspectual classification. A genetic algorithm determines what combinations of linguistic features to use for this task.Comment: postscript, 9 pages, Proceedings of the Second International Conference on New Methods in Language Processing, Oflazer and Somers ed

Cooperative answers in database systems

A major concern of researchers who seek to improve human-computer communication involves how to move beyond literal interpretations of queries to a level of responsiveness that takes the user's misconceptions, expectations, desires, and interests into consideration. At Maryland, we are investigating how to better meet a user's needs within the framework of the cooperative answering system of Gal and Minker. We have been exploring how to use semantic information about the database to formulate coherent and informative answers. The work has two main thrusts: (1) the construction of a logic formula which embodies the content of a cooperative answer; and (2) the presentation of the logic formula to the user in a natural language form. The information that is available in a deductive database system for building cooperative answers includes integrity constraints, user constraints, the search tree for answers to the query, and false presuppositions that are present in the query. The basic cooperative answering theory of Gal and Minker forms the foundation of a cooperative answering system that integrates the new construction and presentation methods. This paper provides an overview of the cooperative answering strategies used in the CARMIN cooperative answering system, an ongoing research effort at Maryland. Section 2 gives some useful background definitions. Section 3 describes techniques for collecting cooperative logical formulae. Section 4 discusses which natural language generation techniques are useful for presenting the logic formula in natural language text. Section 5 presents a diagram of the system

Textual Economy through Close Coupling of Syntax and Semantics

We focus on the production of efficient descriptions of objects, actions and events. We define a type of efficiency, textual economy, that exploits the hearer's recognition of inferential links to material elsewhere within a sentence. Textual economy leads to efficient descriptions because the material that supports such inferences has been included to satisfy independent communicative goals, and is therefore overloaded in Pollack's sense. We argue that achieving textual economy imposes strong requirements on the representation and reasoning used in generating sentences. The representation must support the generator's simultaneous consideration of syntax and semantics. Reasoning must enable the generator to assess quickly and reliably at any stage how the hearer will interpret the current sentence, with its (incomplete) syntax and semantics. We show that these representational and reasoning requirements are met in the SPUD system for sentence planning and realization.Comment: 10 pages, uses QobiTree.te

Generating models for temporal representations

We discuss the use of model building for temporal representations. We chose Polish to illustrate our discussion because it has an interesting aspectual system, but the points we wish to make are not language specific. Rather, our goal is to develop theoretical and computational tools for temporal model building tasks in computational semantics. To this end, we present a first-order theory of time and events which is rich enough to capture interesting semantic distinctions, and an algorithm which takes minimal models for first-order theories and systematically attempts to ``perturb'' their temporal component to provide non-minimal, but semantically significant, models

Kleene Algebras, Regular Languages and Substructural Logics

We introduce the two substructural propositional logics KL, KL+, which use disjunction, fusion and a unary, (quasi-)exponential connective. For both we prove strong completeness with respect to the interpretation in Kleene algebras and a variant thereof. We also prove strong completeness for language models, where each logic comes with a different interpretation. We show that for both logics the cut rule is admissible and both have a decidable consequence relation.Comment: In Proceedings GandALF 2014, arXiv:1408.556

Paracompositionality, MWEs and Argument Substitution

Multi-word expressions, verb-particle constructions, idiomatically combining phrases, and phrasal idioms have something in common: not all of their elements contribute to the argument structure of the predicate implicated by the expression. Radically lexicalized theories of grammar that avoid string-, term-, logical form-, and tree-writing, and categorial grammars that avoid wrap operation, make predictions about the categories involved in verb-particles and phrasal idioms. They may require singleton types, which can only substitute for one value, not just for one kind of value. These types are asymmetric: they can be arguments only. They also narrowly constrain the kind of semantic value that can correspond to such syntactic categories. Idiomatically combining phrases do not subcategorize for singleton types, and they exploit another locally computable and compositional property of a correspondence, that every syntactic expression can project its head word. Such MWEs can be seen as empirically realized categorial possibilities, rather than lacuna in a theory of lexicalizable syntactic categories.Comment: accepted version (pre-final) for 23rd Formal Grammar Conference, August 2018, Sofi