Triple
T6380271
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Autlán de Navarro |
E143561
|
entity |
| Predicate | hasRegionCode |
P3446
|
FINISHED |
| Object | JAL |
E169483
|
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: JAL | Statement: [Autlán de Navarro, hasRegionCode, JAL]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: JAL Context triple: [Autlán de Navarro, hasRegionCode, JAL]
-
A.
JAL
chosen
JAL is the vehicle registration code used on license plates issued in the Mexican state of Jalisco.
-
B.
Japan Airlines
Japan Airlines is the flag carrier of Japan, operating an extensive network of domestic and international flights across Asia, Europe, and the Americas.
-
C.
All Nippon Airways
All Nippon Airways is a major Japanese airline and Star Alliance member known for its extensive domestic and international route network and high service standards.
-
D.
Skymark Airlines
Skymark Airlines is a Japanese low-cost carrier based in Tokyo that operates domestic flights and some international services.
-
E.
Aircalin
Aircalin is the international airline of New Caledonia, operating regional and long-haul flights primarily across the Pacific and to Asia.
- 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_69c008d9f4348190ab598a2913259a1c |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0685265208190b2204bd4abff2668 |
completed | March 22, 2026, 10:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c71a5cf7008190a24ecfeab5acb583 |
completed | March 28, 2026, 12:01 a.m. |
Created at: March 22, 2026, 4:33 p.m.