Triple
T21258693
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gaochang Ruins |
E523938
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Turpan |
—
|
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: Turpan | Statement: [Gaochang Ruins, locatedIn, Turpan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Turpan Context triple: [Gaochang Ruins, locatedIn, Turpan]
-
A.
Turpan
chosen
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.
-
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.
Kashgar
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.
-
D.
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.
-
E.
Korla
Korla is a major oasis city in Xinjiang, China, known as an important transportation and economic hub along the northern edge of the Taklamakan Desert.
- 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_69e0b5156d7881909bd4f83676590715 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e735e477d08190be17ad5384d69a80 |
completed | April 21, 2026, 8:31 a.m. |
Created at: April 16, 2026, 3:59 p.m.