Triple
T22966042
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ziyang |
E571048
|
entity |
| Predicate | neighboringRegion |
P17964
|
FINISHED |
| Object | Meishan |
—
|
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: Meishan | Statement: [Ziyang, neighboringRegion, Meishan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Meishan Context triple: [Ziyang, neighboringRegion, Meishan]
-
A.
Meishan
chosen
Meishan is a county-level city in Sichuan Province, China, known as the hometown of the famous Song dynasty poet Su Shi and for its rich cultural heritage and agricultural surroundings.
-
B.
Emeishan city
Emeishan city is a county-level city in Sichuan Province, China, best known as the gateway to the UNESCO-listed Mount Emei and its surrounding scenic and cultural attractions.
-
C.
Yangzhong
Yangzhong is a county-level city in Jiangsu Province, China, situated on islands in the Yangtze River and administered by the prefecture-level city of Zhenjiang.
-
D.
Quidong
Quidong is a rural locality in New South Wales, Australia, situated within the Snowy Monaro region.
-
E.
Liyang
Liyang is a county-level city in Jiangsu Province, China, known for its scenic attractions such as Tianmu Lake and its administration under the prefecture-level city of Changzhou.
- 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_69e245b2c6548190a0e4c7f2f7df2d48 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1822e542c8190a865f18e64fc0768 |
completed | April 29, 2026, 3:59 a.m. |
Created at: April 17, 2026, 3:47 p.m.