Triple
T19593498
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wei He |
E470293
|
entity |
| Predicate | passesThrough |
P225
|
FINISHED |
| Object | Tianshui |
—
|
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: Tianshui | Statement: [Wei He, passesThrough, Tianshui]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tianshui Context triple: [Wei He, passesThrough, Tianshui]
-
A.
Tianshui
chosen
Tianshui is a historic city in eastern Gansu Province, China, known as an important stop on the ancient Silk Road and for its nearby Maijishan Grottoes.
-
B.
Longnan City
Longnan City is a prefecture-level city in southern Gansu Province, China, known for its mountainous terrain, river valleys, and position as a gateway between northwest and southwest China.
-
C.
Yumen City
Yumen City is a county-level city in Gansu Province, China, historically known as an important stop along the ancient Silk Road and for its oil industry.
-
D.
Dingxi City
Dingxi City is a prefecture-level city in central Gansu Province, China, known for its agriculture-based economy and location on the Loess Plateau.
-
E.
Lanzhou
Lanzhou is a major city in northwestern China and the capital of Gansu Province, known historically as a key hub on the ancient Silk Road.
- 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.