1. SCTB: A Chinese Treebank in Scientific Domain
Chenhui Chu, Toshiaki Nakazawa
Daisuke Kawahara and Sadao Kurohashi
ALR 2016

2. The Significant Needs Increase of Chinese Analysis in Scientific Domain
Intelligent access to Chinese scientific text such as:
Text mining
Knowledge discovery
Translation
China
China
# Scientific papers
# Patents

3. Segmentation and POS tagger
Chinese Analysis
烟草使用者
(tobacco user)
Segmentation and POS tagger
烟草_NN 使用_VV 者_SFN
tobacco use person
Syntactic parser
Treebank

4. Chinese Treebanks
Treebank
Size
Syntactic
structure
Domain
CTB [Xue+ 2005]
18k in CTB5
phrase
News!
PKU [Yu+ 2003]
14k
both
HIT [Che+ 2012]
50k
dependency
There is no available Chinese treebanks in scientific domain!

5. Chinese Analysis Accuracies (with analyzers trained on CTB5)
Solution: construct a Chinese treebank in scientific domain (SCTB)
F-Measure (%)

6. SCTB Annotation: Raw Sentence Selection
Randomly selected from the parallel data in the LCAS (National Science Library, Chinese Academy of Sciences) corpus
As there are corresponding translated Japanese and English sentences, we leave the potential to develop our treebank to a trilingual one

7. SCTB Annotation: Annotation Standard
Phrase structure: Follow the annotation
standard of CTB [Xue+ 2005]
NEW!
POS tagging: follow CTB [Xue+ 2005], but
6 additional tags for bound morphemes
Segmentation: short and consistent units
[Shen+ COLING 2016] 12/13 14:00~
One word in conventional
segmentation standards

8. SCTB Annotation: Annotation Process
Used the SynTree toolkit
　as the annotation interface
Two annotators with inter-annotator agreements of 98.95%, 97.78%, and 95.05% for segmentation, POS tagging and parsing, respectively
Finished 5,133 sentences in 6 month at the submission time of this paper (now about 8,000 sentences)

9. Experimental Settings for Chinese Analysis
Chinese analyzers
KyotoMorph [Shen+ 2014] for segmentation and POS tagging
Berkeley parser [Petrov+ 2007] for syntactic parsing
Comparison: test on 200 scientific sentences
Baseline: trained on CTB5
Baseline+SCTB: additionally added SCTB

10. Chinese Analysis Accuracies with SCTB
F-Measure (%)

11. An Improved Parsing Example
Gold
Baseline
Baseline+SCTB
被动(passive) /肌肉(muscle) / 骨骼(skeleton) /亚(sub) /系统(system)

12. Learning Curve
(%)

13. Machine Translation Experiments
Shared MT Tasks
ASPEC-CJ: Chinese-to-Japanese in scientific domain [Nakazawa+ 2015]
NTCIR-CE: Chinese-to-English in patent domain
[Goto+ 2013]
MT system
Moses tree-to-string [Koehn+ 2007]
System
ASPEC-CJ (BLEU)
NTCIR-CE (BLEU)
Baseline
39.12
33.19
Baseline+SCTB
40.08
33.90

14. An Improved MT Example
Baseline
Baseline+SCTB

15. Conclusion
We constructed SCTB: a Chinese treebank in scientific domain
SCTB 1.0 has been released for free!
Future Work
Annotate more sentences
Develop it to a trilingual treebank