Triple
T20219201
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Canton |
E495205
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | Canton, China |
—
|
NE NERFINISHED |
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, China | Statement: [Canton, namedAfter, Canton, China]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Canton, China Context triple: [Canton, namedAfter, Canton, China]
-
A.
Canton, China
chosen
Canton, China is the former English name for Guangzhou, a major port city in southern China and the capital of Guangdong province.
-
B.
Hsiangcheng, China
Hsiangcheng, China is a town in Henan Province known as the birthplace of author and social critic Os Guinness.
-
C.
City of Canton
The City of Canton is a local municipal government that administers public services and infrastructure, including the Canton Municipal Airport, for its community.
-
D.
Hangtou
Hangtou is a town in Shanghai, China, known as the southern terminus of the Shanghai Metro’s Line 18.
-
E.
Caizhou
Caizhou was a historic Chinese city best known as the final capital of the Jurchen-led Jin dynasty before its fall to the Mongols.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69da626cff80819097b530718a7c98b6 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66edbb67081909c7359ff27205b5f |
completed | April 20, 2026, 6:22 p.m. |
Created at: April 11, 2026, 11:39 p.m.