Triple
T23390689
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yangluo |
E594007
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | Xinzhou 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: Xinzhou District | Statement: [Yangluo, partOf, Xinzhou District]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Xinzhou District Context triple: [Yangluo, partOf, Xinzhou District]
-
A.
Xinzhou District
Xinzhou District is the central urban district and administrative hub of Shangrao City in Jiangxi Province, China.
-
B.
Xinzhou District
chosen
Xinzhou District is an outlying district of Wuhan, China, known for its ongoing urban development and integration into the city’s metro network.
-
C.
Xinzhou
Xinzhou is a prefecture-level city in northern China known for its historical sites and location within Shanxi Province’s coal-rich and culturally significant region.
-
D.
Datong District
Datong District is an urban administrative district under the jurisdiction of Huainan City in Anhui Province, China, known for its role in the region’s coal industry and urban development.
-
E.
Shangzhou District
Shangzhou District is an urban administrative district in Shangluo, Shaanxi Province, China, serving as the city's political and economic center.
- 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_69e25d2754fc819085deea939bde60ab |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1a49bdfec8190afa592c66660c279 |
completed | April 29, 2026, 6:26 a.m. |
Created at: April 17, 2026, 5:35 p.m.