Triple
T31003488
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | easyGroup Holdings Limited |
E790002
|
entity |
| Predicate | licensesBrand |
P78085
|
FINISHED |
| Object | easyJet |
—
|
NE NERFINISHED |
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 | Statement: [easyGroup Holdings Limited, licensesBrand, easyJet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: licensesBrand Context triple: [easyGroup Holdings Limited, licensesBrand, easyJet]
-
A.
brandLicenseFrom
chosen
Indicates that one entity holds a licensed right to use the brand owned or controlled by another entity.
-
B.
licenseManufacturerOf
Indicates that one entity is authorized, via a license, to manufacture products or goods on behalf of or under the rights of another entity.
-
C.
ownsLicensesUnderBrand
Indicates that one entity holds or possesses licenses that are issued under, associated with, or governed by a particular brand.
-
D.
licenseBuiltBy
Indicates that a license was created, issued, or constructed by a specific agent or organization.
-
E.
licenseFocus
Indicates that a license specifically targets, applies to, or is primarily concerned with a particular subject, activity, or scope.
- F. None of above.
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_69f224c65a348190baaed1c01a29900c |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f69dfdda708190be290c7bec205445 |
completed | May 3, 2026, 12:59 a.m. |
| PD | Predicate disambiguation | batch_69f69d1a37e081908d1d86b90ff502bd |
completed | May 3, 2026, 12:55 a.m. |
Created at: April 29, 2026, 8:57 p.m.