Triple
T4220237
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AFR |
E94319
|
entity |
| Predicate | relatedTo |
P37
|
FINISHED |
| Object | Air France |
E16857
|
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: Air France | Statement: [AFR, relatedTo, Air France]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Air France Context triple: [AFR, relatedTo, Air France]
-
A.
Air France
chosen
Air France is the French flag carrier airline and one of Europe’s major international airlines, operating a global network of passenger and cargo services.
-
B.
Air France-KLM
Air France-KLM is a major Franco-Dutch airline holding company and one of Europe’s largest airline groups, operating extensive global passenger and cargo networks.
-
C.
Transavia France
Transavia France is a French low-cost airline and subsidiary of the Air France-KLM group, operating primarily short- and medium-haul leisure routes across Europe and the Mediterranean.
-
D.
French Bee Airlines
French Bee Airlines is a French low-cost, long-haul carrier known for operating budget flights primarily between France, the United States, and various leisure destinations.
-
E.
Lufthansa
Lufthansa is Germany’s largest airline and a major global carrier known for its extensive international network and role in shaping modern airline alliances.
- 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_69b3451997e08190851db4a9a588837d |
completed | March 12, 2026, 10:58 p.m. |
| NER | Named-entity recognition | batch_69b34e0c84548190b051d32d434cbf04 |
completed | March 12, 2026, 11:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b627befdd881908b602fd80f030405 |
completed | March 15, 2026, 3:30 a.m. |
Created at: March 12, 2026, 11:04 p.m.