Triple
T1398313
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | XiamenAir |
E30720
|
entity |
| Predicate | callsign |
P1565
|
FINISHED |
| Object | XIAMEN AIR |
E30720
|
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: XIAMEN AIR | Statement: [XiamenAir, callsign, XIAMEN AIR]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: XIAMEN AIR Context triple: [XiamenAir, callsign, XIAMEN AIR]
-
A.
XiamenAir
chosen
XiamenAir is a Chinese airline based in Xiamen that operates domestic and international flights across Asia and beyond.
-
B.
Shenzhen Airlines
Shenzhen Airlines is a major Chinese carrier based in Shenzhen that operates extensive domestic and regional flights across Asia.
-
C.
Hainan Airlines
Hainan Airlines is a major Chinese airline headquartered in Haikou, known for its extensive domestic and international route network and high service quality ratings.
-
D.
China Southern Airlines
China Southern Airlines is one of China’s largest airlines, operating extensive domestic and international routes from major hubs like Guangzhou and Beijing.
-
E.
Air China
Air China is the flag carrier and one of the largest airlines of the People's Republic of China, operating extensive domestic and international passenger and cargo services.
- 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_69a498fd4e408190bd73eca30ea9754c |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c382b6588190833c39ac84fb6139 |
completed | March 1, 2026, 10:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69acde353b148190b9122f1d6d80fbd4 |
completed | March 8, 2026, 2:25 a.m. |
Created at: March 1, 2026, 7:59 p.m.