Triple
T22966036
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ziyang |
E571048
|
entity |
| Predicate | capitalOf |
P204
|
FINISHED |
| Object | Ziyang 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: Ziyang City | Statement: [Ziyang, capitalOf, Ziyang City]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ziyang City Context triple: [Ziyang, capitalOf, Ziyang City]
-
A.
Ziyang
Ziyang is the art name (courtesy name) of Zhu Xi, the influential Neo-Confucian philosopher of the Southern Song dynasty.
-
B.
Ziyang
chosen
Ziyang is a city in Sichuan Province, China, located within the fertile and densely populated Chengdu Plain region.
-
C.
Zaoyang City
Zaoyang City is a county-level city in Hubei Province, China, known for its historical significance and agricultural production.
-
D.
Xiangyang
Xiangyang is a historic prefecture-level city in northern Hubei Province, China, known for its strategic location on the Han River and well-preserved ancient city walls.
-
E.
Enshi City
Enshi City is a county-level city in southwestern Hubei Province, China, known for its mountainous karst landscapes and role as a cultural center for the Tujia and Miao ethnic groups.
- 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.