Triple
T6263216
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lin Zexu |
E140349
|
entity |
| Predicate | placeOfActivity |
P1527
|
FINISHED |
| Object | Canton |
E55203
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Canton | Statement: [Lin Zexu, placeOfActivity, Canton]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Canton Context triple: [Lin Zexu, placeOfActivity, Canton]
-
A.
Canton
chosen
Canton is the historical Western name for Guangzhou, a major port city in southern China and the capital of Guangdong province.
-
B.
Canton
Canton is a suburban town in Norfolk County, Massachusetts, located southwest of Boston and known for its residential character and local historic sites.
-
C.
Canton
Canton is a historic waterfront neighborhood in southeast Baltimore, Maryland, known for its revitalized harborfront, rowhouses, and vibrant bar and restaurant scene.
-
D.
Canton
Canton is a small New England town in Hartford County, Connecticut, known for its historic village centers and scenic Farmington River setting.
-
E.
Canton
Canton is a city in northeastern Ohio best known as the home of the Pro Football Hall of Fame.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69c008c95c5c819084bd3dd56133d84d |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c06387fec0819095b47a37b9402aa9 |
completed | March 22, 2026, 9:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c5e3f7faf08190a349c9444135afb8 |
completed | March 27, 2026, 1:57 a.m. |
Created at: March 22, 2026, 4:25 p.m.