Triple
T17130365
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sunday Bazaar |
E415706
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Kashgar |
E89243
|
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: Kashgar | Statement: [Sunday Bazaar, locatedIn, Kashgar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kashgar Context triple: [Sunday Bazaar, locatedIn, Kashgar]
-
A.
Kashgar
chosen
Kashgar is an ancient oasis city in western China’s Xinjiang region that long served as a key cultural and commercial crossroads between East and West.
-
B.
Ghulja
Ghulja is the historical name for Yining, a city in China’s Xinjiang region known as a cultural and commercial center in the Ili River valley.
-
C.
Urumqi
Urumqi is the capital of China’s Xinjiang Uyghur Autonomous Region, known as a major cultural and economic hub in Central Asia and one of the most inland major cities in the world.
-
D.
Turpan
Turpan is an oasis city and depression in China’s Xinjiang region, historically a key Silk Road hub known for its extreme heat, ancient irrigation systems, and grape cultivation.
-
E.
Karamay
Karamay is an oil-rich industrial city in northwestern China known for its major petroleum fields and role in the energy industry of Xinjiang.
- 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_69d886d15af4819092f92f8a129763e6 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3f029d1a48190a9d4094827d11d23 |
completed | April 18, 2026, 8:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01414cd5d481908d11eb230d2283cd |
completed | May 11, 2026, 2:39 a.m. |
Created at: April 10, 2026, 5:36 a.m.