Triple
T19154469
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taishan |
E468895
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Xinhui District |
—
|
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: Xinhui District | Statement: [Taishan, borderedBy, Xinhui District]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Xinhui District Context triple: [Taishan, borderedBy, Xinhui District]
-
A.
Xinhui District
chosen
Xinhui District is an urban district of Jiangmen in Guangdong Province, China, known historically as a key overseas Chinese hometown and for its citrus production.
-
B.
Zhuhui District
Zhuhui District is an urban administrative district of Hengyang City in Hunan Province, China, known for its commercial activity and transportation links.
-
C.
Keqiao District
Keqiao District is an urban district of Shaoxing in Zhejiang Province, China, known as a major global center for the textile and fabric trade.
-
D.
Jinshan District
Jinshan District is a suburban coastal district in southwestern Shanghai, known for its petrochemical industry, beaches, and growing residential communities.
-
E.
Jinshan District
Jinshan District is a coastal suburban district in northern Taiwan known for its hot springs, scenic shoreline, and location within New Taipei City.
- 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_69d8dd084ff48190ac0f8c46ee722629 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5eeb81bf08190b0352137eb4a5763 |
completed | April 20, 2026, 9:15 a.m. |
Created at: April 10, 2026, 12:06 p.m.