Triple
T19593497
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wei He |
E470293
|
entity |
| Predicate | passesThrough |
P225
|
FINISHED |
| Object | Weinan |
—
|
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: Weinan | Statement: [Wei He, passesThrough, Weinan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Weinan Context triple: [Wei He, passesThrough, Weinan]
-
A.
Weinan
chosen
Weinan is a prefecture-level city in eastern Shaanxi Province, China, known for its historical sites and location near the Wei River.
-
B.
Lüliang
Lüliang is a prefecture-level city in western Shanxi Province, China, known for its mountainous terrain and significant coal and energy resources.
-
C.
Fenyang
Fenyang is a county-level city in Shanxi Province, China, known for its historical heritage and role in regional commerce and culture.
-
D.
Huayin City
Huayin City is a county-level city in Shaanxi Province, China, best known as the gateway to the famous Mount Hua, one of China’s Five Great Mountains.
-
E.
Tongchuan
Tongchuan is a prefecture-level city in central Shaanxi Province, China, historically known for its coal mining industry and location on the Loess Plateau.
- 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_69d8e510024481908415c0d616fa6186 |
completed | April 10, 2026, 11:54 a.m. |
| NER | Named-entity recognition | batch_69e640782e2c8190b5baef07a2bdd015 |
completed | April 20, 2026, 3:04 p.m. |
Created at: April 10, 2026, 1:43 p.m.