75 research outputs found
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
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Planning multisentential English text using communicative acts
The goal of this research is to develop explanation presentation mechanisms for knowledge based
systems which enable them to define domain terminology and concepts, narrate events, elucidate plans,
processes, or propositions and argue to support a claim or advocate action. This requires the development
of devices which select, structure, order and then linguistically realize explanation content as coherent and
cohesive English text.
With the goal of identifying generic explanation presentation strategies, a wide range of naturally
occurring texts were analyzed with respect to their communicative sttucture, function, content and intended
effects on the reader. This motivated an integrated theory of communicative acts which characterizes text at
the level of rhetorical acts (e.g., describe, define, narrate), illocutionary acts (e.g., inform, request), and
locutionary acts (e.g., ask, command). Taken as a whole, the identified communicative acts characterize
the structure, content and intended effects of four types of text: description, narration, exposition,
argument. These text types have distinct effects such as getting the reader to know about entities, to know
about events, to understand plans, processes, or propositions, or to believe propositions or want to
perform actions. In addition to identifying the communicative function and effect of text at multiple levels
of abstraction, this dissertation details a tripartite theory of focus of attention (discourse focus, temporal
focus, and spatial focus) which constrains the planning and linguistic realization of text.
To test the integrated theory of communicative acts and tripartite theory of focus of attention, a text
generation system TEXPLAN (Textual EXplanation PLANner) was implemented that plans and
linguistically realizes multisentential and multiparagraph explanations from knowledge based systems. The
communicative acts identified during text analysis were formalized as over sixty compositional and (in
some cases) recursive plan operators in the library of a hierarchical planner. Discourse, temporal, and
spatial focus models were implemented to track and use attentional information to guide the organization
and realization of text. Because the plan operators distinguish between the communicative function (e.g.,
argue for a proposition) and the expected effect (e.g., the reader believes the proposition) of communicative
acts, the system is able to construct a discourse model of the structure and function of its textual responses
as well as a user model of the expected effects of its responses on the reader's knowledge, beliefs, and
desires. The system uses both the discourse model and user model to guide subsequent utterances. To test
its generality, the system was interfaced to a variety of domain applications including a neuropsychological
diagnosis system, a mission planning system, and a knowledge based mission simulator. The system
produces descriptions, narrations, expositions, and arguments from these applications, thus exhibiting a
broader range of rhetorical coverage than previous text generation systems
Natural language generation in the LOLITA system an engineering approach
Natural Language Generation (NLG) is the automatic generation of Natural Language (NL) by computer in order to meet communicative goals. One aim of NL processing (NLP) is to allow more natural communication with a computer and, since communication is a two-way process, a NL system should be able to produce as well as interpret NL text. This research concerns the design and implementation of a NLG module for the LOLITA system. LOLITA (Large scale, Object-based, Linguistic Interactor, Translator and Analyser) is a general purpose base NLP system which performs core NLP tasks and upon which prototype NL applications have been built. As part of this encompassing project, this research shares some of its properties and methodological assumptions: the LOLITA generator has been built following Natural Language Engineering principles uses LOLITA's SemNet representation as input and is implemented in the functional programming language Haskell. As in other generation systems the adopted solution utilises a two component architecture. However, in order to avoid problems which occur at the interface between traditional planning and realisation modules (known as the generation gap) the distribution of tasks between the planner and plan-realiser is different: the plan-realiser, in the absence of detailed planning instructions, must perform some tasks (such as the selection and ordering of content) which are more traditionally performed by a planner. This work largely concerns the development of the plan- realiser and its interface with the planner. Another aspect of the solution is the use of Abstract Transformations which act on the SemNet input before realisation leading to an increased ability for creating paraphrases. The research has lead to a practical working solution which has greatly increased the power of the LOLITA system. The research also investigates how NLG systems can be evaluated and the advantages and disadvantages of using a functional language for the generation task
Approximate text generation from non-hierarchical representations in a declarative framework
This thesis is on Natural Language Generation. It describes a linguistic realisation
system that translates the semantic information encoded in a conceptual graph into an
English language sentence. The use of a non-hierarchically structured semantic representation (conceptual graphs) and an approximate matching between semantic structures allows us to investigate a more general version of the sentence generation problem
where one is not pre-committed to a choice of the syntactically prominent elements in
the initial semantics. We show clearly how the semantic structure is declaratively related to linguistically motivated syntactic representation — we use D-Tree Grammars
which stem from work on Tree-Adjoining Grammars. The declarative specification of
the mapping between semantics and syntax allows for different processing strategies
to be exploited. A number of generation strategies have been considered: a pure topdown strategy and a chart-based generation technique which allows partially successful
computations to be reused in other branches of the search space. Having a generator
with increased paraphrasing power as a consequence of using non-hierarchical input
and approximate matching raises the issue whether certain 'better' paraphrases can be
generated before others. We investigate preference-based processing in the context of
generation
From chance to choice : the development of teachers in a postmodern world.
SIGLEAvailable from British Library Document Supply Centre- DSC:DX185932 / BLDSC - British Library Document Supply CentreGBUnited Kingdo
Meat: A Novel
An English-language translation of a Russian novel that appeared in the Soviet thick journal Novyi Mir in three installments during February, March, and April of 1936
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