Triple
T4421639
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TO |
E95110
|
entity |
| Predicate | assignedToAirline |
P41156
|
FINISHED |
| Object | Transavia France |
E17177
|
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: Transavia France | Statement: [TO, assignedToAirline, Transavia France]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Transavia France Context triple: [TO, assignedToAirline, Transavia France]
-
A.
Transavia France
chosen
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.
-
B.
Transavia
Transavia is a Dutch low-cost airline operating scheduled and charter flights across Europe and North Africa.
-
C.
Brussels Airlines
Brussels Airlines is the flag carrier airline of Belgium, operating flights across Europe, Africa, and other regions as part of the Lufthansa Group.
-
D.
Martinair
Martinair is a Dutch airline based in the Netherlands that operates both cargo and charter passenger services, historically linked to KLM.
-
E.
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.
- 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_69b3453a36908190b95a79a297ca083c |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3554a0e7c8190b704d00d07b1857d |
completed | March 13, 2026, 12:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5f62715748190abceb14396ad637d |
completed | March 14, 2026, 11:58 p.m. |
Created at: March 12, 2026, 11:30 p.m.