Triple
T5846792
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Korla |
E129730
|
entity |
| Predicate | airport |
P1065
|
FINISHED |
| Object | Korla Airport |
E553757
|
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: Korla Airport | Statement: [Korla, airport, Korla Airport]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Korla Airport Context triple: [Korla, airport, Korla Airport]
-
A.
Korla Airport
chosen
Korla Airport is a regional civil airport serving the city of Korla in Xinjiang, China, providing both passenger and cargo air services.
-
B.
Hotan Airport
Hotan Airport is a regional civil airport serving the city of Hotan in Xinjiang, China, providing both passenger and limited cargo air services.
-
C.
Urumqi Diwopu International Airport
Urumqi Diwopu International Airport is a major international airport in Ürümqi, Xinjiang, serving as a key aviation gateway between China and Central Asia.
-
D.
Andijan Airport
Andijan Airport is a regional public airport serving the city of Andijan in eastern Uzbekistan, handling domestic flights and limited international services.
-
E.
Zhuliany Airport
Zhuliany Airport is a major international airport serving Kyiv, Ukraine, known for its proximity to the city center and focus on regional and low-cost flights.
- 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_69c0084bd31c8190a796bb6284845e83 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0351157508190a78d2a7141e0cee8 |
completed | March 22, 2026, 6:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0bfd6cffc8190b65252f02055e89c |
completed | March 23, 2026, 4:21 a.m. |
Created at: March 22, 2026, 3:55 p.m.