Triple
T19214347
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ximen Station |
E480441
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Wanhua 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: Wanhua District | Statement: [Ximen Station, locatedIn, Wanhua District]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wanhua District Context triple: [Ximen Station, locatedIn, Wanhua District]
-
A.
Wanhua District
chosen
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.
-
B.
Chengzhong District
Chengzhong District is a central urban district of Xining, the capital city of Qinghai Province in northwest China.
-
C.
Tianxin District
Tianxin District is a central urban district of Changsha, the capital city of Hunan Province in China, known for its historical sites and commercial areas.
-
D.
Wanghua District
Wanghua District is an urban district of the city of Fushun in Liaoning Province, northeastern China, known for its role in the region’s industrial and residential development.
-
E.
Jianhua District
Jianhua District is a central urban district of Qiqihar City in Heilongjiang Province, northeastern 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_69d8e8cb8c348190b52075823911c869 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fa397c188190b85bcfd9afd8dce6 |
completed | April 20, 2026, 10:04 a.m. |
Created at: April 10, 2026, 1:22 p.m.