Triple
T22563097
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pingtan County |
E557868
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | Fuzhou City |
—
|
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: Fuzhou City | Statement: [Pingtan County, partOf, Fuzhou City]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fuzhou City Context triple: [Pingtan County, partOf, Fuzhou City]
-
A.
Fuzhou
chosen
Fuzhou is the capital and largest city of China’s Fujian Province, known as a major coastal and river port with a long history of maritime trade and cultural exchange.
-
B.
Xiamen
Xiamen is a major coastal city in southeastern China known for its port, tourism, and historic role as one of the country’s earliest Special Economic Zones.
-
C.
Zhangzhou
Zhangzhou is a historic coastal city in southeastern China known for its agriculture, traditional Minnan culture, and proximity to Xiamen in Fujian Province.
-
D.
Nanping
Nanping is a prefecture-level city in northern Fujian Province, China, known for its mountainous terrain, rich biodiversity, and role as a regional transport and economic hub.
-
E.
Nanping
Nanping is a town-level division within Yixian County in China, known as one of its local administrative settlements.
- 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_69e11e5ae4ac8190b1f503457603d969 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15fa7a828819096804ac928e2aaf9 |
completed | April 29, 2026, 1:32 a.m. |
Created at: April 16, 2026, 8:52 p.m.