Triple
T2563374
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Qing army |
E57292
|
entity |
| Predicate | garrisonedIn |
P2911
|
FINISHED |
| Object | Lanzhou |
E76473
|
NE FINISHED |
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: Lanzhou | Statement: [Qing army, garrisonedIn, Lanzhou]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lanzhou Context triple: [Qing army, garrisonedIn, Lanzhou]
-
A.
Lanzhou
chosen
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.
-
B.
Yinchuan
Yinchuan is the capital and largest city of the Ningxia Hui Autonomous Region in north-central China, known for its historical Silk Road significance and rapidly developing economy.
-
C.
Xining
Xining is the capital and largest city of Qinghai Province in western China, known as a key hub on the Tibetan Plateau and a historic gateway between Han Chinese and Tibetan regions.
-
D.
Yining
Yining is a city in the Ili Kazakh Autonomous Prefecture of far northwestern China, known for its diverse ethnic population and role as a regional trade and cultural center.
-
E.
Wuhai
Wuhai is a prefecture-level industrial city in western Inner Mongolia, China, known for its coal mining, chemical industries, and location along the Yellow River.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ab4a4ef9008190a0e6d4422b9418b7 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd3374c648190a29b2cc209d66668 |
completed | March 7, 2026, 7:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af5d264db481908e9dc3b5e2e8260a |
completed | March 9, 2026, 11:52 p.m. |
Created at: March 6, 2026, 9:48 p.m.