Coping with Uncertainty: Noun Phrase Interpretation and Early Semantic Analysis

A computer program which can "understand" natural language texts must have both syntactic knowledge about the language concerned and semantic knowledge of how what is written relates to its internal representation of the world. It has been a matter of some controversy how these sources of information can best be integrated to translate from an input text to a formal meaning representation. The controversy has concerned largely the question as to what degree of syntactic analysis must be performed before any semantic analysis can take place. An extreme position in this debate is that a syntactic parse tree for a complete sentence must be produced before any investigation of that sentence's meaning is appropriate. This position has been criticised by those who see understanding as a process that takes place gradually as the text is read, rather than in sudden bursts of activity at the ends of sentences. These people advocate a model where semantic analysis can operate on fragments of text before the global syntactic structure is determined - a strategy which we will call early semantic analysis. In this thesis, we investigate the implications of early semantic analysis in the interpretation of noun phrases. One possible approach is to say that a noun phrase is a self-contained unit and can be fully interpreted by the time it has been read. Thus it can always be determined what objects a noun phrase refers to without consulting much more than the structure of the phrase itself. This approach was taken in part by Winograd [Winograd 72], who saw the constraint that a noun phrase have a referent as a valuable aid in resolving local syntactic ambiguity. Unfortunately, Winograd's work has been criticised by Ritchie, because it is not always possible to determine what a noun phrase refers to purely on the basis of local information. In this thesis, we will go further than this and claim that, because the meaning of a noun phrase can be affected by so many factors outside the phrase itself, it makes no sense to talk about "the referent" as a function of -a noun phrase. Instead, the notion of "referent" is something defined by global issues of structure and consistency. Having rejected one approach to the early semantic analysis of noun phrases, we go on to develop an alternative, which we call incremental evaluation. The basic idea is that a noun phrase does provide some information about what it refers to. It should be possible to represent this partial information and gradually refine it as relevant implications of the context are followed up. Moreover, the partial information should be available to an inference system, which, amongst other things, can detect the absence of a referent and provide the advantages of Winograd's system. In our system, noun phrase interpretation does take place locally, but the point is that it does not finish there. Instead, the determination of the meaning of a noun phrase is spread over the subsequent analysis of how it contributes to the meaning of the text as a whole

Incremental Interpretation: Applications, Theory, and Relationship to Dynamic Semantics

Why should computers interpret language incrementally? In recent years psycholinguistic evidence for incremental interpretation has become more and more compelling, suggesting that humans perform semantic interpretation before constituent boundaries, possibly word by word. However, possible computational applications have received less attention. In this paper we consider various potential applications, in particular graphical interaction and dialogue. We then review the theoretical and computational tools available for mapping from fragments of sentences to fully scoped semantic representations. Finally, we tease apart the relationship between dynamic semantics and incremental interpretation.Comment: Procs. of COLING 94, LaTeX (2.09 preferred), 8 page

Anaphora and Discourse Structure

We argue in this paper that many common adverbial phrases generally taken to signal a discourse relation between syntactically connected units within discourse structure, instead work anaphorically to contribute relational meaning, with only indirect dependence on discourse structure. This allows a simpler discourse structure to provide scaffolding for compositional semantics, and reveals multiple ways in which the relational meaning conveyed by adverbial connectives can interact with that associated with discourse structure. We conclude by sketching out a lexicalised grammar for discourse that facilitates discourse interpretation as a product of compositional rules, anaphor resolution and inference.Comment: 45 pages, 17 figures. Revised resubmission to Computational Linguistic

SCREEN: Learning a Flat Syntactic and Semantic Spoken Language Analysis Using Artificial Neural Networks

In this paper, we describe a so-called screening approach for learning robust processing of spontaneously spoken language. A screening approach is a flat analysis which uses shallow sequences of category representations for analyzing an utterance at various syntactic, semantic and dialog levels. Rather than using a deeply structured symbolic analysis, we use a flat connectionist analysis. This screening approach aims at supporting speech and language processing by using (1) data-driven learning and (2) robustness of connectionist networks. In order to test this approach, we have developed the SCREEN system which is based on this new robust, learned and flat analysis. In this paper, we focus on a detailed description of SCREEN's architecture, the flat syntactic and semantic analysis, the interaction with a speech recognizer, and a detailed evaluation analysis of the robustness under the influence of noisy or incomplete input. The main result of this paper is that flat representations allow more robust processing of spontaneous spoken language than deeply structured representations. In particular, we show how the fault-tolerance and learning capability of connectionist networks can support a flat analysis for providing more robust spoken-language processing within an overall hybrid symbolic/connectionist framework.Comment: 51 pages, Postscript. To be published in Journal of Artificial Intelligence Research 6(1), 199

Papers on predicative constructions : Proceedings of the workshop on secundary predication, October 16-17, 2000, Berlin

This volume presents a collection of papers touching on various issues concerning the syntax and semantics of predicative constructions. A hot topic in the study of predicative copula constructions, with direct implications for the treatment of he (how many he's do we need?), and wider implications for the theories of predication, event-based semantics and aspect, is the nature and source of the situation argument. Closer examination of copula-less predications is becoming increasingly relevant to all these issues, as is clearly illustrated by the present collection

Graph Interpolation Grammars: a Rule-based Approach to the Incremental Parsing of Natural Languages

Graph Interpolation Grammars are a declarative formalism with an operational semantics. Their goal is to emulate salient features of the human parser, and notably incrementality. The parsing process defined by GIGs incrementally builds a syntactic representation of a sentence as each successive lexeme is read. A GIG rule specifies a set of parse configurations that trigger its application and an operation to perform on a matching configuration. Rules are partly context-sensitive; furthermore, they are reversible, meaning that their operations can be undone, which allows the parsing process to be nondeterministic. These two factors confer enough expressive power to the formalism for parsing natural languages.Comment: 41 pages, Postscript onl

A Transition-Based Directed Acyclic Graph Parser for UCCA

We present the first parser for UCCA, a cross-linguistically applicable framework for semantic representation, which builds on extensive typological work and supports rapid annotation. UCCA poses a challenge for existing parsing techniques, as it exhibits reentrancy (resulting in DAG structures), discontinuous structures and non-terminal nodes corresponding to complex semantic units. To our knowledge, the conjunction of these formal properties is not supported by any existing parser. Our transition-based parser, which uses a novel transition set and features based on bidirectional LSTMs, has value not just for UCCA parsing: its ability to handle more general graph structures can inform the development of parsers for other semantic DAG structures, and in languages that frequently use discontinuous structures.Comment: 16 pages; Accepted as long paper at ACL201