High precision treebanking - blazing useful trees using POS information
In this paper we present a quantitative and qualitative analysis of annotation in the Hinoki treebank of Japanese, and investigate a method of speeding annotation by using part...
Saved in:
Main Authors: | , , , |
---|---|
Other Authors: | |
Format: | Conference or Workshop Item |
Language: | English |
Published: |
2011
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/79569 http://hdl.handle.net/10220/6820 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
id |
sg-ntu-dr.10356-79569 |
---|---|
record_format |
dspace |
spelling |
sg-ntu-dr.10356-795692020-03-07T12:10:36Z High precision treebanking - blazing useful trees using POS information Tanaka, Takaaki Bond, Francis Oepen, Stephan Fujita, Sanae School of Humanities and Social Sciences Annual Meeting on Association for Computational Linguistics (43rd : 2005) DRNTU::Humanities::Linguistics::Sociolinguistics::Computational linguistics In this paper we present a quantitative and qualitative analysis of annotation in the Hinoki treebank of Japanese, and investigate a method of speeding annotation by using part-of-speech tags. The Hinoki treebank is a Redwoods-style treebank of Japanese dictionary de nition sentences. 5,000 sentences are annotated by three different annotators and the agreement evaluated. An average agreement of 65.4% was found using strict agreement, and 83.5% using labeled precision. Exploiting POS tags allowed the annotators to choose the best parse with 19.5% fewer decisions. Published version 2011-06-13T05:55:19Z 2019-12-06T13:28:27Z 2011-06-13T05:55:19Z 2019-12-06T13:28:27Z 2005 2005 Conference Paper Tanaka, T., Bond, F., Oepen, S., & Fujita, S. (2005). High precision treebanking - blazing useful trees using POS information. Proceedings of the 43rd Annual Meeting of the ACL, 330-337. https://hdl.handle.net/10356/79569 http://hdl.handle.net/10220/6820 10.3115/1219840.1219881 155529 en © 2005 ACL. This paper was published in Proceedings of the 43rd Annual Meeting of the ACL and is made available as an electronic reprint (preprint) with permission of Association for Computational Linguistics. The paper can be found at: [DOI: http://dx.doi.org/10.3115/1219840.1219881]. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper is prohibited and is subject to penalties under law. 8 p. application/pdf |
institution |
Nanyang Technological University |
building |
NTU Library |
country |
Singapore |
collection |
DR-NTU |
language |
English |
topic |
DRNTU::Humanities::Linguistics::Sociolinguistics::Computational linguistics |
spellingShingle |
DRNTU::Humanities::Linguistics::Sociolinguistics::Computational linguistics Tanaka, Takaaki Bond, Francis Oepen, Stephan Fujita, Sanae High precision treebanking - blazing useful trees using POS information |
description |
In this paper we present a quantitative
and qualitative analysis of annotation in
the Hinoki treebank of Japanese, and investigate
a method of speeding annotation
by using part-of-speech tags. The Hinoki
treebank is a Redwoods-style treebank of
Japanese dictionary de nition sentences.
5,000 sentences are annotated by three different
annotators and the agreement evaluated.
An average agreement of 65.4% was
found using strict agreement, and 83.5%
using labeled precision. Exploiting POS
tags allowed the annotators to choose the
best parse with 19.5% fewer decisions. |
author2 |
School of Humanities and Social Sciences |
author_facet |
School of Humanities and Social Sciences Tanaka, Takaaki Bond, Francis Oepen, Stephan Fujita, Sanae |
format |
Conference or Workshop Item |
author |
Tanaka, Takaaki Bond, Francis Oepen, Stephan Fujita, Sanae |
author_sort |
Tanaka, Takaaki |
title |
High precision treebanking - blazing useful trees using POS information |
title_short |
High precision treebanking - blazing useful trees using POS information |
title_full |
High precision treebanking - blazing useful trees using POS information |
title_fullStr |
High precision treebanking - blazing useful trees using POS information |
title_full_unstemmed |
High precision treebanking - blazing useful trees using POS information |
title_sort |
high precision treebanking - blazing useful trees using pos information |
publishDate |
2011 |
url |
https://hdl.handle.net/10356/79569 http://hdl.handle.net/10220/6820 |
_version_ |
1681043938069184512 |