Alejandra

Regional Distrito Capital | Centro de Gestión AdministrativaEspecialidad: Tecnólogo Gestión EmpresarialCompetencia: Producción de textos en Ingles Actividad: Trabajo FinalAprendiz: Quira Alejandra Herrera Camelo – Juan Sebastian Castro Celis Grupo: 179549 | Fecha:Pág: |
Discourse Structure and Text Planning
Objectives
Investigate thestructure of multisentence discourse, monologues and dialogues, and build text planning (and sentence planning) systems to plan coherent multisentence texts.
Approach
The internal structure of discourse and the computational planning and generation of coherent multisentential paragraphs has been a topic of investigation at USC/ISI since the early 1980's. A theory of the interclausal relationships thatgovern discourse structure, called Rhetorical Structure Theory (RST), was developed in [Mann and Thompson 88] after extensive analysis of hundreds of texts of various genres. The analysis concluded that English text is coherent by virtue of so-called rhetorical relations that hold between clauses and blocks of clauses, and identified about 25 basic relations for English. These relations, such asSequence, Purpose, and Elaboration are usually identified in
English by key words or phrases (such as "then", "in order to", and "e.g.", respectively).
In order to plan multisentence paragraphs by computer, one requires both a sound theory of text organization and an algorithm that can make efficient use of it. The theory is provided by RST; the algorithm by an adaptation of the top-downhierarchical expansion planning system NOAH developed in AI in the 1970's. A text structure planner was developed at USC/ISI to plan coherent paragraphs which achieve communicative goals of affecting the hearer's knowledge in some way [Hovy 88]. The planner operated in conjunction with some application program (such as a database access system or expert system) and employed the Penman generator togenerate individual sentences. Using operationalized RST relations and other text plans, the planner constructed a tree that embodied the paragraph structure, in which nonterminal nodes were RST relations and terminal nodes contained the material to be communicated. This text planning process has been extended by several other projects at USC/ISI and elsewhere. In a separate project, members of theEES/EXPECT project at USC/ISI built the EES text planner along the same lines as the initial Penman text structurer, incorporating an expanded text plan library using a notation oriented toward intentionality [Moore 89]. This planner's text plan contains the intentional, attentional, and rhetorical structures of the explanations it generates for EES expert systems.
A later research effort studied thenumber of interclausal discourse structure relations. [Hovy and Maier 93] collected and taxonomized over 300 relations from a variety of sources into three taxonomies of 120 relations altogether. A second effort performed at USC/ISI involved the automated planning of certain types of text formatting. In [Hovy and Arens 91], the communicative semantics of certain text formatting devices (such asenumerated lists, itemizations, footnotes, appendices, etc.) is described in terms of RST relations, and the automated planning of formatted paragraphs of text is illustrated.
A general overview of the text planning work appears in [Hovy 93].
Current work focuses on two aspects: a better understanding of discourse structure and the construction of various modules of a sentence planner (includingclause aggregation, sentence scoping, reference, and some aspects of lexical choice). The sentence planner is being tested in the Spangloss machine translation project.
Text Planning
Although the process of content determination has worked through a number of moves that may be made in the generated text, the result is not the kind of tree structure that one needs for realisation and also has...