Triple
T13014855
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Quanshan District |
E322522
|
entity |
| Predicate | borderingEntity |
P224
|
FINISHED |
| Object | Yunlong District |
E321380
|
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: Yunlong District | Statement: [Quanshan District, borderingEntity, Yunlong District]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yunlong District Context triple: [Quanshan District, borderingEntity, Yunlong District]
-
A.
Yunlong District
chosen
Yunlong District is an urban administrative district and central area of Xuzhou City in Jiangsu Province, China.
-
B.
Yuanbaoshan District
Yuanbaoshan District is an urban administrative district within the city of Chifeng in Inner Mongolia, China.
-
C.
Yangmei District
Yangmei District is an urban and industrial district in southwestern Taoyuan City, Taiwan, known for its manufacturing hubs and growing residential communities.
-
D.
Xialu District
Xialu District is an urban administrative district of the prefecture-level city of Huangshi in Hubei Province, China.
-
E.
Tianya District
Tianya District is an administrative district of the city of Sanya in Hainan Province, China, known for its coastal tourism and tropical scenery.
- 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_69d807657e8c8190bd9435ee2f823845 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97ecd04748190ade2530ee5db35fe |
completed | April 10, 2026, 10:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7b8c0b24c819082d0ec947b7d99ea |
completed | May 3, 2026, 9:06 p.m. |
Created at: April 9, 2026, 8:50 p.m.