Triple
T11175685
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Philippines AirAsia |
E264405
|
entity |
| Predicate | callsign |
P1565
|
FINISHED |
| Object | AIRASIA |
E398414
|
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: AIRASIA | Statement: [Philippines AirAsia, callsign, AIRASIA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: AIRASIA Context triple: [Philippines AirAsia, callsign, AIRASIA]
-
A.
AirAsia
chosen
AirAsia is a Malaysian low-cost airline known for its extensive network of domestic and international routes across Asia and beyond.
-
B.
Thai AirAsia
Thai AirAsia is a Thai low-cost airline operating domestic and international flights, and is part of the wider AirAsia group based in Southeast Asia.
-
C.
AirAsia Indonesia
AirAsia Indonesia is a low-cost airline based in Indonesia and a subsidiary of the Malaysia-based AirAsia Group, operating domestic and international flights across Asia.
-
D.
EVA Air
EVA Air is a major Taiwanese international airline known for its extensive global route network, high service standards, and innovative themed flights such as its Hello Kitty jets.
-
E.
Akasa Air
Akasa Air is an Indian low-cost airline that began operations in 2022, offering domestic flights with a focus on affordable fares and a modern fleet.
- 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_69d6aa9dafac8190bd90d2c74f661aa7 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8987e1081909b28a0bdb866beae |
completed | April 9, 2026, 5:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e4cc0f84008190b5306323aff4a300 |
completed | April 19, 2026, 12:35 p.m. |
Created at: April 8, 2026, 9:29 p.m.