Left-right trees, a new tree structure for machine translation.

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Title: Left-right trees, a new tree structure for machine translation.
Authors: Kurokawa, Kouichi1, Kasai, Takumi1
Source: Systems & Computers in Japan. 5/1/1998, Vol. 29 Issue 5, p84-91. 8p.
Subjects: Translators (Computer programs), Automation, Grammar, Comparative grammar, English language, Transducers
Abstract: This paper describes a new tree structure called the left-right tree, along with its grammar and automaton, which form the theoretical basis for an English-Japanese machine translator developed by the authors. A left-right tree is a tree that differentiates between left children and right children. An English sentence is transformed into a set of left-right trees by labeling each node of the left-right tree with an English word. To represent a language, which is a collection of such left-right trees, we define a grammar for left-right tree languages, called the “tree categorical grammar.” We also define the valenced pushdown transducer as a formalized model of the parser used in the translator. Due to the valence property of the symbols, the work of the stack is restricted in the pushdown transducer. We demonstrate the equivalence of the classes of left-right tree languages produced by different representations and explain some of the properties satisfied by the classes. © 1998 Scripta Technica, Syst Comp Jpn, 29(5): 84–91, 1998 [ABSTRACT FROM AUTHOR]
Copyright of Systems & Computers in Japan is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: <searchLink fieldCode="JN" term="%22Systems+%26+Computers+in+Japan%22">Systems & Computers in Japan</searchLink>. 5/1/1998, Vol. 29 Issue 5, p84-91. 8p.
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  Data: <searchLink fieldCode="DE" term="%22Translators+%28Computer+programs%29%22">Translators (Computer programs)</searchLink><br /><searchLink fieldCode="DE" term="%22Automation%22">Automation</searchLink><br /><searchLink fieldCode="DE" term="%22Grammar%22">Grammar</searchLink><br /><searchLink fieldCode="DE" term="%22Comparative+grammar%22">Comparative grammar</searchLink><br /><searchLink fieldCode="DE" term="%22English+language%22">English language</searchLink><br /><searchLink fieldCode="DE" term="%22Transducers%22">Transducers</searchLink>
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  Data: This paper describes a new tree structure called the left-right tree, along with its grammar and automaton, which form the theoretical basis for an English-Japanese machine translator developed by the authors. A left-right tree is a tree that differentiates between left children and right children. An English sentence is transformed into a set of left-right trees by labeling each node of the left-right tree with an English word. To represent a language, which is a collection of such left-right trees, we define a grammar for left-right tree languages, called the “tree categorical grammar.” We also define the valenced pushdown transducer as a formalized model of the parser used in the translator. Due to the valence property of the symbols, the work of the stack is restricted in the pushdown transducer. We demonstrate the equivalence of the classes of left-right tree languages produced by different representations and explain some of the properties satisfied by the classes. © 1998 Scripta Technica, Syst Comp Jpn, 29(5): 84–91, 1998 [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Systems & Computers in Japan is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1002/(SICI)1520-684X(199805)29:5<84::AID-SCJ9>3.0.CO;2-J
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      – SubjectFull: Grammar
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              Text: 5/1/1998
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              Y: 1998
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