A simple unification method for CFG
Rule-based machine translation is an approach that uses linguistic information in order to translate. Various formalisms, such as LFG2 , and HPSG3, GPSG4, which are based on CFG, can be used as the underlying formalism in machine translation. These grammars perform unification in order to check the...
Saved in:
Main Author: | |
---|---|
Format: | text |
Published: |
Animo Repository
2022
|
Subjects: | |
Online Access: | https://animorepository.dlsu.edu.ph/faculty_research/5175 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | De La Salle University |
id |
oai:animorepository.dlsu.edu.ph:faculty_research-6044 |
---|---|
record_format |
eprints |
spelling |
oai:animorepository.dlsu.edu.ph:faculty_research-60442022-04-05T08:30:12Z A simple unification method for CFG Fontanilla, Gian Kristian A. Rule-based machine translation is an approach that uses linguistic information in order to translate. Various formalisms, such as LFG2 , and HPSG3, GPSG4, which are based on CFG, can be used as the underlying formalism in machine translation. These grammars perform unification in order to check the functional well-formedness of a sentence, which is particularly useful in translation. However, the unification approach employed by these grammars is diagnostic, which is of limited use during transfer and generation. Unification-based grammars also require extensive linguistic information, such as the schemata in LFG, which is difficult to build given limited language resources and experts. In this paper, a simple corrective unification method is presented, which is to be used alongside a standard CFG. This unification method can be used to maintain language phenomena, such as subject-verb agreement in English, among others. This unification method is used by a hybrid machine translation system for Filipino-English called HyFilEngMT. 2022-04-06T04:06:31Z text https://animorepository.dlsu.edu.ph/faculty_research/5175 Faculty Research Work Animo Repository Machine translating Computer Sciences |
institution |
De La Salle University |
building |
De La Salle University Library |
continent |
Asia |
country |
Philippines Philippines |
content_provider |
De La Salle University Library |
collection |
DLSU Institutional Repository |
topic |
Machine translating Computer Sciences |
spellingShingle |
Machine translating Computer Sciences Fontanilla, Gian Kristian A. A simple unification method for CFG |
description |
Rule-based machine translation is an approach that uses linguistic information in order to translate. Various formalisms, such as LFG2 , and HPSG3, GPSG4, which are based on CFG, can be used as the underlying formalism in machine translation. These grammars perform unification in order to check the functional well-formedness of a sentence, which is particularly useful in translation. However, the unification approach employed by these grammars is diagnostic, which is of limited use during transfer and generation. Unification-based grammars also require extensive linguistic information, such as the schemata in LFG, which is difficult to build given limited language resources and experts. In this paper, a simple corrective unification method is presented, which is to be used alongside a standard CFG. This unification method can be used to maintain language phenomena, such as subject-verb agreement in English, among others. This unification method is used by a hybrid machine translation system for Filipino-English called HyFilEngMT. |
format |
text |
author |
Fontanilla, Gian Kristian A. |
author_facet |
Fontanilla, Gian Kristian A. |
author_sort |
Fontanilla, Gian Kristian A. |
title |
A simple unification method for CFG |
title_short |
A simple unification method for CFG |
title_full |
A simple unification method for CFG |
title_fullStr |
A simple unification method for CFG |
title_full_unstemmed |
A simple unification method for CFG |
title_sort |
simple unification method for cfg |
publisher |
Animo Repository |
publishDate |
2022 |
url |
https://animorepository.dlsu.edu.ph/faculty_research/5175 |
_version_ |
1767196268690407424 |