Triple
T1054880
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Xinjiang |
E22779
|
entity |
| Predicate | largestCity |
P235
|
FINISHED |
| Object | Ürümqi |
E138505
|
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: Ürümqi | Statement: [Xinjiang, largestCity, Ürümqi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ürümqi Context triple: [Xinjiang, largestCity, Ürümqi]
-
A.
Ürümqi
chosen
Ürümqi is a major city in northwestern China that serves as the political, economic, and cultural center of the Xinjiang Uyghur Autonomous Region.
-
B.
Karaganda
Karaganda is a large industrial city in central Kazakhstan known for its coal mining industry and Soviet-era history.
-
C.
Namangan
Namangan is a major city in eastern Uzbekistan, known as an important cultural and economic center in the Fergana Valley.
-
D.
Shymkent
Shymkent is one of the largest and most populous cities in southern Kazakhstan, serving as a key industrial, commercial, and cultural center of the region.
-
E.
Andijan
Andijan is a historic city in eastern Uzbekistan, known as a major cultural and economic center of the Fergana Valley and as the birthplace of the Mughal emperor Babur.
- 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_69a493da02e081908c13ff5e02a0fe7a |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b8d79268819080f3f3f497e91c58 |
completed | March 1, 2026, 10:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac8303cbec8190a3b8a9bad2434ee7 |
completed | March 7, 2026, 7:56 p.m. |
Created at: March 1, 2026, 7:42 p.m.