Triple
T15081475
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Huzhou |
E360154
|
entity |
| Predicate | hasDistrict |
P459
|
FINISHED |
| Object | Wuxing District |
E1061057
|
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: Wuxing District | Statement: [Huzhou, hasDistrict, Wuxing District]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wuxing District Context triple: [Huzhou, hasDistrict, Wuxing District]
-
A.
Wuxing District
chosen
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.
-
B.
Xiangfang District
Xiangfang District is an urban district of Harbin in Heilongjiang Province, China, known for its industrial base and role in the city's economic development.
-
C.
Jinyuan District
Jinyuan District is an urban administrative district of Taiyuan, the capital city of Shanxi Province in northern China.
-
D.
Wanhua District
Wanhua District is one of Taipei’s oldest urban areas, known for its historic temples, traditional markets, and the popular shopping and entertainment area of Ximending.
-
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_69d85a035aa88190b52a139d3a1b7b6d |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0027450a48190a84588b6aaf84ebf |
completed | April 15, 2026, 9:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a002d92c9788190aa4523a1e47bc561 |
completed | May 10, 2026, 7:02 a.m. |
Created at: April 10, 2026, 3:03 a.m.