Triple
T5811236
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hotan |
E128870
|
entity |
| Predicate | hasAirport |
P105
|
FINISHED |
| Object |
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.
|
E551312
|
NE FINISHED |
How this triple was built (4 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: Hotan Airport | Statement: [Hotan, hasAirport, Hotan Airport]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hotan Airport Context triple: [Hotan, hasAirport, Hotan Airport]
-
A.
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.
-
B.
Bannu Airport
Bannu Airport is a domestic airport serving the city of Bannu in Khyber Pakhtunkhwa, Pakistan.
-
C.
Bamyan Airport
Bamyan Airport is a small regional airfield in central Afghanistan that serves the city of Bamyan and provides access to the surrounding mountainous province.
-
D.
Hotan
Hotan is an oasis city in southwestern Xinjiang, China, historically known as a key Silk Road hub famed for its jade, silk, and carpets.
-
E.
Zhob Airport
Zhob Airport is a domestic airport serving the city of Zhob in Balochistan, Pakistan, providing regional air connectivity.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Hotan Airport Triple: [Hotan, hasAirport, Hotan Airport]
Generated description
Hotan Airport is a regional civil airport serving the city of Hotan in Xinjiang, China, providing both passenger and limited cargo air services.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hotan Airport Target entity description: Hotan Airport is a regional civil airport serving the city of Hotan in Xinjiang, China, providing both passenger and limited cargo air services.
-
A.
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.
-
B.
Bannu Airport
Bannu Airport is a domestic airport serving the city of Bannu in Khyber Pakhtunkhwa, Pakistan.
-
C.
Bamyan Airport
Bamyan Airport is a small regional airfield in central Afghanistan that serves the city of Bamyan and provides access to the surrounding mountainous province.
-
D.
Hotan
Hotan is an oasis city in southwestern Xinjiang, China, historically known as a key Silk Road hub famed for its jade, silk, and carpets.
-
E.
Zhob Airport
Zhob Airport is a domestic airport serving the city of Zhob in Balochistan, Pakistan, providing regional air connectivity.
- F. None of above. chosen
Provenance (5 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_69c0084788848190bcf71f6bc5d71597 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02b538cd08190a7dac378898059b9 |
completed | March 22, 2026, 5:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0a1826cc081909572d9bf99d5f670 |
completed | March 23, 2026, 2:12 a.m. |
| NEDg | Description generation | batch_69c0a210d9788190b3a40e8ec2f2c6b6 |
completed | March 23, 2026, 2:14 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c0a2afcef88190a77c8089a1b85393 |
completed | March 23, 2026, 2:17 a.m. |
Created at: March 22, 2026, 3:52 p.m.