1. Grammar correction – Data collection interface
David Ling

2. Contents Background Data collection plan
Data collection system (progress report)

3. Background Project in charge: Target: Method:
Holly Chung, Amy Kwok, Anora Wong (ENG)
Target:
English error corrections for HK students
Highlight good practices (not well defined yet)
Method:
Chollampatt, 2018
Fairseq (Facebook) + Language model (KenLM)
Math lessons use English.  Math lessons are conducted in English.
Better than traditional rule based (eg. Word, Grammarly)

4. Grammar correction data set
LANG-8 (Japan social website)
NUCLE (National University of Singapore)

5. Grammar correction data set
Building a data set for Hong Kong students
Improvement on the checker
Different sentence style
Different error types
Literature value
statistical analysis on HK students’ English

6. Grammar correction data set
Daniel Dahlmeier, Building a Large Annotated Corpus of Learner English: The NUS Corpus of Learner English, ACL 2013
Course assignments
A wide range of topics, like technology innovation or health care

7. Grammar correction data set
NUCLE DATA SAMPLE
28 error types: Verb tense, Subject-verb-agreement, Article or Determiner, Noun Number, …
10 English instructors
7 months

8. Data collection plan
Timeline proposed by Amy
Review and modify the tag sets (adding HK style tag)
Hire teachers for tagging and proposed: HK$100 per essay x 2,000 essays = HK$200,000
Data set: internal use/ open to public / commercial?

9. Marking tool
Marking tool = Data base (sqlite) + Interface (PHP + javascript)
Data base: essays + annotations
Currently implemented features
Login, listing database essays, annotate, save and remove annotation
DEMO:
Teacher Teacher Teacher