Triple
T17850067
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dayuan District |
E445775
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Xinwu 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: Xinwu District | Statement: [Dayuan District, borderedBy, Xinwu District]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Xinwu District Context triple: [Dayuan District, borderedBy, Xinwu District]
-
A.
Xinwu District
chosen
Xinwu District is an urban district of Wuxi in Jiangsu Province, China, known for its industrial development and modern infrastructure.
-
B.
Xinwu District
Xinwu District is a coastal rural district in southwestern Taoyuan City, Taiwan, known for its agriculture, traditional Hakka culture, and seaside landscapes.
-
C.
Jiang'an District
Jiang'an District is an urban district of Wuhan in Hubei Province, China, known for its central location and role as a key commercial and residential area of the city.
-
D.
Wuxing District
Wuxing District is an urban district of Huzhou in Zhejiang Province, China, known as a historic and economic center in the northern part of the province.
-
E.
Qiaocheng District
Qiaocheng District is the central urban district and core administrative area of Bozhou in Anhui Province, China.
- 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_69d8b9f26f18819089c9e43250bee6ae |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e48ffe415c8190aed351c52b78a143 |
completed | April 19, 2026, 8:19 a.m. |
Created at: April 10, 2026, 10:16 a.m.