Triple
T107603
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charles de Gaulle Airport |
E2173
|
entity |
| Predicate | hubFor |
P423
|
FINISHED |
| Object | easyJet Europe |
E6907
|
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: easyJet Europe | Statement: [Charles de Gaulle Airport, hubFor, easyJet Europe]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: easyJet Europe Context triple: [Charles de Gaulle Airport, hubFor, easyJet Europe]
-
A.
easyJet
chosen
easyJet is a major British low-cost airline operating extensive domestic and European routes.
-
B.
Ryanair
Ryanair is a major Irish low-cost airline known for its extensive network of short-haul flights across Europe.
-
C.
Jet2.com
Jet2.com is a British low-cost leisure airline that operates scheduled and charter flights across Europe from multiple UK bases.
-
D.
JetBlue Airways
JetBlue Airways is a major American low-cost airline known for its customer-friendly service, free in-flight entertainment, and extensive route network across the United States, Caribbean, and Latin America.
-
E.
Manchester Airports Group
Manchester Airports Group is a leading UK-based airport operator that owns and manages several major airports, including Manchester, London Stansted, and East Midlands.
- 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_69a24fcdaeb48190a2d796677e4b3281 |
completed | Feb. 28, 2026, 2:15 a.m. |
| NER | Named-entity recognition | batch_69a256cac6d4819083b50c9c9d95e975 |
completed | Feb. 28, 2026, 2:45 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a275e81aa48190827b634822e25058 |
completed | Feb. 28, 2026, 4:58 a.m. |
Created at: Feb. 28, 2026, 2:20 a.m.