Triple
T10001533
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wenzhou |
E197338
|
entity |
| Predicate | hasDistrict |
P459
|
FINISHED |
| Object | Lucheng District |
E882910
|
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: Lucheng District | Statement: [Wenzhou, hasDistrict, Lucheng District]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lucheng District Context triple: [Wenzhou, hasDistrict, Lucheng District]
-
A.
Lucheng District
chosen
Lucheng District is the central urban district and administrative, commercial, and cultural core of Wenzhou in Zhejiang Province, China.
-
B.
Hecheng District
Hecheng District is the central urban district and administrative seat of Huaihua in Hunan Province, China.
-
C.
Licheng District
Licheng District is a central urban district of Quanzhou in Fujian Province, China, known for its historic architecture and cultural heritage.
-
D.
Lianyun District
Lianyun District is an urban coastal district of Lianyungang in Jiangsu Province, China, known for its port facilities and seaside location on the Yellow Sea.
-
E.
Zhengxiang District
Zhengxiang District is an urban administrative district of Hengyang City in Hunan Province, China, known for its role as one of the city's central built-up areas.
- 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_69ca82f3b61c81908ecc2c1c96dbc2e4 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdcc8f50888190b2f1c5240cb58e4f |
completed | April 2, 2026, 1:55 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69de54a30b748190bb791078e9dde442 |
completed | April 14, 2026, 2:52 p.m. |
Created at: March 30, 2026, 8:51 p.m.