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Paper Abstract and Keywords
Presentation 2010-08-06 11:05
A Phase Theory-Based Computational Model of Sentence Generation
Jason Ginsburg (Univ. of Aizu.) TL2010-27
Abstract (in Japanese) (See Japanese page) 
(in English) This paper presents a computational model of sentence generation, based on recent work in Phase Theory (Chomsky 1999, 2004, 2006), that attempts to replicate on a computer the innate structures of the mind that enable humans to produce and understand sentences. We created a computer model (implemented in Python) that derives a sentence from a numeration, where a numeration is a set of subnumerations, and a subnumeration is a set of Lexical Items (LIs) that corresponds to a v* (v*P) or C* (CP) phase, or to a phrase that must be formed outside the main spine of a derivation (subjects and adjuncts). A sentence is constructed from the bottom up starting with the most embedded subnumeration. A subnumeration is emptied out via a process of selection and Merge of LIs to form a derivational tree. Once a subnumeration is emptied, the LIs of a higher subnumeration, if present, are selected and Merged with the derivational tree. The end result, if the derivation does not crash, is a complete and well-formed sentence of a language. This model attempts to clarify the somewhat vague process, utilized within Phase Theory, of selection of LIs from a subnumeration via the following basic algorithm: 1) search for an element that a feature checking relation can be established with, 2) otherwise, select an element with an Edge feature according to a predefined selection order (elements on the left, if present, are selected first): N>D >V >v*>T>C*. For example, the program derives the sentence tree '[TP I [v* I(copy) eat food]]' from the subnumeration '{C*, [T PRES], {v* , { D, [N I]}, [V eat] ,[N food]}}'. To construct a V projection (VP), V (with an Edge feature) is selected from the subnumeration and Merged with a D (DP) that is already in the derivational workspace. V assigns a theta-role to D, and then V's Edge feature disappears. Next v* is selected from the subnumeration, and the process of selection and Merge continues. We demonstrate how this model successfully derives sentences in English and Japanese, for which the only differences are the lexicons and the ordering of elements that have been Merged. This model shows that a limited amount of built in grammatical structure can be utilized to create a wide variety of sentences in various languages and thus, it can be utilized to help further understanding of how humans process language.
Keyword (in Japanese) (See Japanese page) 
(in English) syntax / Phase Theory / computational modeling / numeration / Merge / / /  
Reference Info. IEICE Tech. Rep., vol. 110, no. 163, TL2010-27, pp. 93-98, Aug. 2010.
Paper # TL2010-27 
Date of Issue 2010-07-29 (TL) 
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
Copyright
and
reproduction		 All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF TL2010-27

Conference Information
Committee TL  
Conference Date 2010-08-05 - 2010-08-06 
Place (in Japanese) (See Japanese page) 
Place (in English) Kikai-Shinko-Kaikan Bldg. 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Human Sentence Processing and Production/learning 
Paper Information
Registration To TL 
Conference Code 2010-08-TL 
Language English 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A Phase Theory-Based Computational Model of Sentence Generation 
Sub Title (in English)  
Keyword(1) syntax  
Keyword(2) Phase Theory  
Keyword(3) computational modeling  
Keyword(4) numeration  
Keyword(5) Merge  
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1st Author's Name Jason Ginsburg  
1st Author's Affiliation University of Aizu (Univ. of Aizu.)
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Speaker Author-1 
Date Time 2010-08-06 11:05:00 
Presentation Time 30 minutes 
Registration for TL 
Paper # TL2010-27 
Volume (vol) vol.110 
Number (no) no.163 
Page pp.93-98 
#Pages 6 
Date of Issue 2010-07-29 (TL) 

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