Triple
T13014856
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Quanshan District |
E322522
|
entity |
| Predicate | borderingEntity |
P224
|
FINISHED |
| Object | Tongshan District |
E325450
|
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: Tongshan District | Statement: [Quanshan District, borderingEntity, Tongshan District]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tongshan District Context triple: [Quanshan District, borderingEntity, Tongshan District]
-
A.
Tongshan District
chosen
Tongshan District is an administrative district of the city of Xuzhou in Jiangsu Province, China, known for its mix of urban development and surrounding rural areas.
-
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.
Jinyuan District
Jinyuan District is an urban administrative district of Taiyuan, the capital city of Shanxi Province in northern China.
-
D.
Qingshan District
Qingshan District is an urban district of Wuhan in Hubei Province, China, known for its heavy industry and riverside location along the Yangtze River.
-
E.
Xiaonan District
Xiaonan District is the central urban district and administrative seat of Xiaogan City in Hubei Province, China.
- 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_69f7c0d12cd88190b6e205ad98296ed9 |
completed | May 3, 2026, 9:40 p.m. |
Created at: April 9, 2026, 8:50 p.m.