Empirical Study of Predictive Powers of Simple Attachment Schemes for Post-modifier Prepositional Phrases

35814

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Abstract

This empirical study attempts to find answers to the question of how a natural language (henceforth NL) system could resolve attachment of preposi- tional phrases (henceforth PPs) by examining nat- urally occurring PP attachments in typed dialogue. Examination includes testing predictive powers of existing attachment theories against the data. The result of this effort will be an algorithm for inter- preting PP attachment.

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Empirical Study of Predictive Powers of Simple Attachment Schemes for Post-modifier Prepositional Phrases Greg Whittemore Kathleen Ferrara Electronic Data Systems Corp. Texas A&~M University 5951 Jefferson Street N.E. Albuquerque, NM 87109-3432 Hans Brunner US West Advanced Technologies 6 June 1990 Abstract This empirical study attempts to find answers to the question of how a natural language (henceforth NL) system could resolve attachment of preposi- tional phrases (henceforth PPs) by examining nat- urally occurring PP attachments in typed dialogue. Examination includes testing predictive powers of existing attachment theories against the data. The result of this effort will be an algorithm for inter- preting PP attachment. Introduction Difficulty in resolving structural ambiguity in- volving PPs arises because of the great variety of syntactic structures which PPs can modify and the varying distances PPs may be from the con- stituents with which they are associated. Simple schemes to resolve attachments utilize information drawn from reported tendencies in the human pars- ing mechanism, such as the preference for PPs to attach to constituents that immediately precede them. It is always tempting to utilize such schemes in computer NL processors because they provide clear models for resolution that are both easy and cheap (in terms of steps involved) to implement. The problem with these schemes is that they can easily be made to fail by manipulating parameters that they 'know' nothing about, such as semantics, context, and intonation. Clearly, more elaborate schemes for attachment resolution are needed, but what these schemes should contain and how they should be implemented remain open. This study attempts to find answers to the ques- tion of how a computer program should resolve at- tachment by examining naturally occurring PP at- tachments in a typed dialogue domain drawn from a study by Brunner, Whittemore, Ferrara, and Hsu (1989). Various previously developed theories of PP attachment are tested against the data to see how well they predict correct attachments of PPs in the typed dialogues. The result of this effort will be a hypothesis of attachment resolution that seems to fit the data. Empirical overview The methods for generating the 13 naturally oc- curring dialogues are described in Brunner, et al. (1989). In essence, this study employed a "wiz- ard of Oz" paradigm in which a human confeder- ate -- the Wizard - simulates an advanced com- puter system engaged in written/interactive dia- logue with the experimental participant. Partici- pants of the study were each asked to plan a spe- cific travel agenda of their choice with information obtained solely by typing natural language mes- sages and requests through a VT220 terminal to a human-assisted travel information system located in a separate room. In response to this, the Wizard, who had access to both computerized and hard- copy travel data, was instructed to engage in con- structive and free-form dialogue with the partici- pant in order to best obtain the reservations and flight information required by them. Each dialogue took one and a half hours to complete, allowing enough time for …

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Labeled Text

This empirical study attempts to find answers to the question of how a natural language (henceforth NL) system could resolve attachment of preposi- tional phrases (henceforth PPs) by examining nat- urally occurring PP attachments in typed dialogue. Examination includes testing predictive powers of existing attachment theories against the data. The result of this effort will be an algorithm for inter- preting PP attachment.

Publication Details

Paper ID:
35814
Year:
1990
Publication:
TIPSTER
Publication Type:
conf
DOI:
nan