Comments (1)
This sounds like a brilliant solution when compared to our previous approach. And you are right, this makes things for a human reader much clearer, as the structure you are proposing inherently draws attention to what's unclear.
Also, just to follow up on LDM, as this logically would result in either of the two things:
- the character LDM provided is still ambiguous, as the relevant syllable segment, for example
MCInitial=[dr/tr]
, is ambiguous - the character is not ambiguous anymore, as LDM refers to the syllable segment that is clear, for example
MCRime=jang|MCTone=X
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Related Issues (20)
- update README
- implement pipeline pattern for data transformations HOT 1
- generate CoNLL-U base versions of all texts
- add logging HOT 1
- fix missing pages in SBCK edition of the JDSW
- add visualization HOT 1
- run topic modeling algorithm on annotations HOT 1
- parse annotations using a model HOT 2
- restructure as spaCy project
- find named entities in annotations HOT 2
- use SuPaR-Kanbun as the base model
- check to see whether NER patterns occur in annotation corpus HOT 1
- rearrange POS tags in priority order HOT 1
- train a span categorizer on jeff & hantao's data HOT 2
- add a streamlit interface for testing named entity predictions HOT 1
- add a streamlit interface for testing span categorization
- Add project task to export annotations
- Separate relation and span annotation
- Detect and label restatements of the headword HOT 1
- Add an algorithm for inferring relations between spans HOT 1
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