Dynamic Semantics of Plurals DPLQ⊛

AbstractThis paper proposes a dynamic semantics of plurals, DPL⊛Q, that is an extension of DPL [8] by adding binary generalized quantifiers, plural terms with join-operators as in Link [17]'s semilattice semantics of plurals, dynamic selectors, dynamic distributors and division functions. DPL⊛Q provides a formalism for handling dependent plurals, bound plurals, generic plurals, and ambiguity of collective/distributive/cumulative interpretation of plurals

Resolving anaphoric references on deficient syntactic descriptions

Syntactic coindexing restrictions are by now known to be of central importance to practical anaphor resolution approaches. Since, in particular due to structural ambiguity, the assumption of the availability of a unique syntactic reading proves to be unrealistic, robust anaphor resolution relies on techniques to overcome this deficiency. In this paper, two approaches are presented which generalize the verification of coindexing constraints to de cient descriptions. At first, a partly heuristic method is described, which has been implemented. Secondly, a provable complete method is specified. It provides the means to exploit the results of anaphor resolution for a further structural disambiguation. By rendering possible a parallel processing model, this method exhibits, in a general sense, a higher degree of robustness. As a practically optimal solution, a combination of the two approaches is suggested

CLiFF Notes: Research In Natural Language Processing at the University of Pennsylvania

CLIFF is the Computational Linguists\u27 Feedback Forum. We are a group of students and faculty who gather once a week to hear a presentation and discuss work currently in progress. The \u27feedback\u27 in the group\u27s name is important: we are interested in sharing ideas, in discussing ongoing research, and in bringing together work done by the students and faculty in Computer Science and other departments. However, there are only so many presentations which we can have in a year. We felt that it would be beneficial to have a report which would have, in one place, short descriptions of the work in Natural Language Processing at the University of Pennsylvania. This report then, is a collection of abstracts from both faculty and graduate students, in Computer Science, Psychology and Linguistics. We want to stress the close ties between these groups, as one of the things that we pride ourselves on here at Penn is the communication among different departments and the inter-departmental work. Rather than try to summarize the varied work currently underway at Penn, we suggest reading the abstracts to see how the students and faculty themselves describe their work. The report illustrates the diversity of interests among the researchers here, as well as explaining the areas of common interest. In addition, since it was our intent to put together a document that would be useful both inside and outside of the university, we hope that this report will explain to everyone some of what we are about

A shallow processing approach to anaphor resolution

The thesis describes an investigation of the feasibility of resolving anaphors in natural language texts by means of a "shallow processing" approach which exploits knowledge of syntax, semantics and local focussing as heavily as possible; it does not rely on the presence of large amounts of world or domain knowledge, which are notoriously hard to process accurately. The ideas reported are implemented in a program called SPAR (Shallow Processing Anaphor Resolver), which resolves anaphoric and other linguistic ambiguities in simple English stories and generates sentence-by-sentence paraphrases that show what interpretations have been selected. Input to SPAR takes the form of semantic structures for single sentences constructed by Boguraev's English analyser. These structures are integrated into a network-style text representation as processing proceeds. To achieve anaphor resolution, SPAR combines and develops several existing techniques, most notably Sidner's theory of local focussing and Wilks' "preference semantics" theory of semantics and common sense inference. Consideration of the need to resolve several anaphors in the same sentence results in Sidner's framework being modified and extended to allow focus-based processing to interact more flexibly with processing based on other types of knowledge. Wilks' treatment of common sense inference is extended to incorporate a wider range of types of inference without jeopardizing its uniformity and simplicity. Further, his primitive-based formalism for word sense meanings is developed in the interests of economy, accuracy and ease of use. Although SPAR is geared mainly towards resolving anaphors, the design of the system allows many non-anaphoric (lexical and structural) ambiguities that cannot be resolved during sentence analysis to be resolved as a by-product of anaphor resolution

Demonstrative anaphora: forms and functions in full-text scientific articles

This study examines the functions and characteristics of demonstrative anaphora (this, these, that, those) in a collection of full-text scientific documents, confirming that they play an important role in maintaining discourse focus and binding together cohesive sections of text. Unlike corpora in other subject domains, the Cystic Fibrosis database contains more demonstrative expressions than other class of anaphora. As participants in intersentential reference, demonstratives often refer to complex propositions rather than simple noun phrases. While this tendency complicates automated resolution, our results yield some suggestions toward a resolution algorithm. Primarily, we argue for the incorporation of demonstrative form since different types of demonstratives show different patterns regarding antecedent length and composition. Although further analysis is necessary, our findings provide a groundwork for future exploration

Generating referring expressions in a domain of objects and processes

This thesis presents a collection of algorithms and data structures for the generation of pronouns, anaphoric definite noun phrases, and one-anaphoric phrases. After a close analysis of the particular kinds of referring expressions that appear in a particular domain -that of cookery recipes -the thesis presents an appropriate ontology and a corresponding representation language. This ontology is then integrated into a wider framework for language generation as a whole, whereupon we show how the representation language can be successfully used to produce appropriate referring expressions for a range of complex object types.Amongst the more important ideas explored in the thesis are the following:• We introduce the notion of a generalized physical object as a way of representing singular entities, mass entities, and entities which are sets.• We adopt the view that planning operators are essentially underspecified events, and use this, in conjunction with a simple model of the hearer, to allow us to determine the appropriate level of detail at which a given plan should be described.• We make use of a discourse model that distinguishes local and global focus, and is closely tied to a notion of discourse structure; and we introduce a notion of DISCRIMINATORY POWER as a means to choosing the content of a referring expression.• We present a model of the generation of referring expressions that makes use of two levels of intermediate representation, and integrate this model with the use of a linguistically- founded grammar for noun phrases.The thesis ends by making some suggestions for further extensions to the work reported here

Towards a Neuroscientific Theory of Reference

The topic of the dissertation is reference of proper names. It criticizes the amalgam of the current standard theory, direct-causal theory of reference, and defends Fregean sense theory of reference. In addition Fregean view is neuronaturalized by Gerald Edelman's idea of recurrent networks, combined with temporal synchrony of neural processing which is generalized to explain conceptual information. Direct-causal theory's main arguments - modal, epistemological and semantic - are all shown to be too weak and based on mistaken presuppositions like synonymy between proper names and descriptions. Causal communicative links are shown to be weak for reference retention also. Intentions to retain the original referent are too weal as well. Moreover the "intuitive arguments" invoked by the direct-causal theorists are misguided and shown to be based on basic schema of reference, a postulation proposed to explain precondition of referential language use. Reference is grounded on information transmission and its embodiment in neurocognitive processes mainly having to do with neural memory systems. So contrary to the direct-causal theorists' view reference is cognitive through and through as Fregean theory maintains. Classical problems in philosophy of language, like informationality of identity statements, propositional attitude contexts, among others, are solved.Väitöksen aihe erisnimien viittaus. Siinä kritisoidaan vallitsevaa teoria-amalgaamia, suora kausaalinen viittauksen teoria. Työssä puolustetaan fregeläistä viittauksen merkitysteoriaa, joka tieteellistetään neuronaturalisoimalla se. Tässä käytetään takaisinpäin vaikuttavia neuronisysteemeitä sekä neuraali-impulssien prosessointisyknroniaa. Suoran kausaalisen teorian keskeiset argumentit osoitetaan riittämättömiksi samoin kuin kausaaliset viittausmekanismit sekä viittausintentiot. Lisäksi kyseisen teorian "intuitiiviset argumentit" osoitetaan perustuvan väärinymmärrykseen ja selitetään työssä postuloituun viittauksen perusskeemaan perustuviksi. Tämä skeema selittää kielellisten ilmausten viittauksen edellytyksen. Viittaus on informaation välitykseen ja neurokognitiivisiin prosesseihin perustuvaa, fregeläisen teorian mukaisesti. Työ antaa tälle näkemykselle neurotieteellisen viitekehyksen

Anaphora in natural language understanding : a survey

A problem that all computer-based natural language understanding (NLU) systems encounter is that of linguistic reference, and in particular anaphora (abbreviated reference). For example, in a text as simple as: Nadia showed sue her new car. orange. The seats were Day-Glo knowing that "her" probably means Nadia and not Sue and that "the seats" means the seats of Nadia's new car is not a simple task. This thesis is an extensive review of the reference and anaphor problem, and the approaches to it that NLU systems have taken, from early systems such as STUDENT through to current discourse-oriented ones such as PAL. The problem is first examined in detail, and examples are given of many different types of anaphor, some of which have been ignored by previous authors. The approaches taken in traditional systems are then described and abstracted and it is shown why they were inadequate, and why discourse theme and anaphoric focus need to be taken into account. The strengths and weaknesses of current anaphora theories and approaches are evaluated . The thesis closes with a list of some remaining research problems. The thesis has been written so as to be as comprehensible as possible to both AI workers who know no linguistics, and linguists who have not studied artificial intelligence

Natural language interface for programming MOO environments

Thesis (S.M.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2008.Includes bibliographical references (leaves 69-70).MOOIDE is an interface to allow novice users to program a MOO environment using natural language. Programming the MOO involves a variety of tasks like creating objects and their states, assigning verb actions to objects, and programming behavior that changes states of objects and generates messages. Once the MOO is programmed, other users can interact with the objects for entertainment or educational purpose. To make MOO programming easier and more accessible to novice programmers, our natural language interface allows users to describe different MOO programming tasks in English. These include adding objects, object properties, states and relationships between objects. They also include verbs through which behaviors are accessed in the MOO. Users can use English to describe decision statements, loops, conditions and other typical programming constructs. Earlier systems focused on addressing parsing issues in programming. However, those systems lacked commonsense knowledge. MOOIDE brings commonsense features to natural language programming in addition to parsing. Commonsense reasoning allows MOOIDE to automatically include typical object properties, verb affordances and affordance rules as well as typical verb effects. Such augmentation of natural language programming with commonsense reasoning capabilities can help make programming significantly more intuitive to novice programmers.by Moinuddin Ahmad.S.M