1,976 research outputs found
Expressing OWL axioms by English sentences: dubious in theory, feasible in practice
With OWL (Web Ontology Language) established as a standard for encoding ontologies on the Semantic Web, interest has begun to focus on the task of verbalising OWL code in controlled English (or other natural language). Current approaches to this task assume that axioms in OWL can be mapped to sentences in English. We examine three potential problems with this approach (concerning logical sophistication, information structure, and size), and show that although these could in theory lead to insuperable difficulties, in practice they seldom arise, because ontology developers use OWL in ways that favour a transparent mapping. This result is evidenced by an analysis of patterns from a corpus of over 600,000 axioms
in about 200 ontologies
Precision and mathematical form in first and subsequent mentions of numerical facts and their relation to document structure
In a corpus study we found that authors vary both mathematical form and precision when expressing numerical quantities. Indeed, within the same document, a quantity is often described vaguely in some places and more accurately in others. Vague descriptions tend to occur early in a document and to be expressed in simpler mathematical forms (e.g., fractions or ratios), whereas more accurate descriptions of the same proportions tend to occur later, often expressed in more complex forms (e.g., decimal percentages). Our results can be used in Natural Language Generation (1) to generate repeat descriptions within the same document, and (2) to generate descriptions of numerical quantities for different audiences according to mathematical ability
Towards a generation-based semantic web authoring tool
Widespread use of Semantic Web technologies requires interfaces through which knowledge can be viewed and edited without deep understanding of Description Logic and formalisms like OWL and RDF. Several groups are pursuing approaches based on Controlled Natural Languages (CNLs), so that editing can be performed by typing in sentences which are automatically interpreted as statements in OWL. We suggest here a variant of this approach which relies entirely on Natural Language Generation (NLG), and propose requirements for a system that can reliably generate transparent realisations of statements in Description Logic
Automatic generation of large-scale paraphrases
Research on paraphrase has mostly focussed on lexical or syntactic variation within individual sentences. Our concern is with larger-scale paraphrases, from multiple sentences or paragraphs to entire documents. In this paper
we address the problem of generating paraphrases of large chunks of texts. We ground our discussion through a
worked example of extending an existing NLG system to accept as input a source text, and to generate a range of fluent semantically-equivalent alternatives, varying not only at the lexical and syntactic levels, but also in document structure and layout
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A Formal Dialogue Model for Ontology Authoring
Several research teams have proposed controlled fragments of English suitable for building ontologies for the Semantic Web. These Controlled Languages are typically employed in applications that allow users to compose texts through guided authoring; the sentences in the text are parsed and interpreted to obtain axioms in OWL. We investigate here a variant of this approach in which the user enters sentences one at a time through an instant messaging interface, and receives an immediate response in English from the authoring system before typing in the next sentence. Such an application can support a variety of dialogue moves by the user—not only assertions, but also retractions, questions, requests for explanation, and so forth—and for each, we need to define an appropriate set of responses for the authoring system. To illustrate the interest and complexity of this task, we develop a formal model for just one case: responses to an assertion
Intuitive querying of e-Health data repositories
At the centre of the Clinical e-Science Framework (CLEF) project is a repository of well organised, detailed clinical histories, encoded as data that will be available for use in clinical care and in-silico medical experiments. An integral part of the CLEF workbench is a tool to allow biomedical researchers and clinicians to query – in an intuitive way – the repository of patient data. This paper describes the CLEF query editing interface, which makes use of natural language generation techniques in order to alleviate some of the problems generally faced by natural language and graphical query interfaces. The query interface also incorporates an answer renderer that dynamically generates responses in both natural language text and graphics
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Dialogue Games for Crosslingual Communication
We describe a novel approach to crosslingual dialogue that supports highly accurate communication of semantically complex content between people who do not speak the same language. The approach is introduced through an implemented application that covers the same ground as the chapter of a conventional phrase book for food shopping. We position the approach with respect to dialogue systems and Machine Translation-based approaches to crosslingual dialogue. The current work is offered as a first step towards the innovative use of dialogue theories for the enhancement of human–human dialogue
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Generating monologue and dialogue to present personalised medical information to patients
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Deriving rhetorical complexity data from the RST-DT Corpus
This paper describes a study of the levels at which different rhetorical relations occur in rhetorical structure trees. In a previous empirical study (Williams and Reiter, 2003) of the RST-DT (Rhetorical Structure Theory Discourse Treebank) Corpus (Carlson et al., 2003), we noticed that certain rhetorical relations tended to occur more frequently at higher levels in a rhetorical structure tree, whereas others seemed to occur more often at lower levels. The present study takes a closer look at the data, partly to test this observation, and partly to investigate related issues such as the relative complexity of satellite and nucleus for each type of relation. One practical application of this investigation would be to guide discourse planning in Natural Language Generation (NLG), so that it reflects more accurately the structures found in documents written by human authors. We present our preliminary findings and discuss their relevance for discourse planning
The Influence of layout on the interpretation of referring expressions
From the introduction: The division of text into visual segments such as sentences, paragraphs and sections achieves many functions, such as easing navigation, achieving pragmatic effect, improving readability and
reflecting the organisation of information (Wright, 1983; Schriver 1997). In this paper, we report a small experiment that investigates the effect of different layout configurations on the interpretation of the antecedent of anaphoric referring expressions. Layout has so far played little role in Natural Language Generation (NLG) systems. The layout of output texts is generally very simple. At worst, it consists of only a single paragraph consisting of a few sentences; at best it is predetermined by schemas (Coch, 1996; Porter and Lester, 1997) or discourse plans (Milosavljevic, 1999). However, recent work by Power (2000) and Bouayad et al. (2000) has integrated graphically signalled segments (e.g., by whitespace, punctuation, font and face alternation) such as paragraphs, lists, text-sentences and text-clauses in a hierarchical tree-like representation called the document structure.2 This work was carried out within the ICONOCLAST
project (Integrating CONstraints On Layout and Style), which aims at automatically generating formatted texts in which the formatting decisions affect the wording and vice-versa.3 If document structure affects the comprehensibility of referring expressions, this must be taken into account in any attempt to generate felicitous formatted texts. This will go a step further from
current research in the automatic generation of referring expressions, where only the effect of discourse structure and grammatical function has been investigated (Dale and Reiter, 1995; Cristea et al., 1998;Walker et al., 1998; Kibble and Power, 1999)
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