Triple
T344454
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | easyJet |
E6907
|
entity |
| Predicate | routeNetworkFocus |
P8860
|
FINISHED |
| Object | point-to-point short-haul routes |
—
|
LITERAL 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: point-to-point short-haul routes | Statement: [easyJet, routeNetworkFocus, point-to-point short-haul routes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: routeNetworkFocus Context triple: [easyJet, routeNetworkFocus, point-to-point short-haul routes]
-
A.
routeNetworkCharacteristic
chosen
Indicates a relationship where a specific characteristic or property is attributed to a route within a network.
-
B.
route
Indicates that one entity serves as a path or course used to travel or move between locations associated with another entity.
-
C.
streetNetwork
Indicates the layout and connectivity relationships among streets within a geographic area, including how roads intersect, link, and form a navigable network.
-
D.
approachRoute
Indicates the path or method taken by one entity as it moves toward or comes closer to another entity or target.
-
E.
routeNumber
Indicates the specific identifying number assigned to a route within a transportation or delivery network.
- 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_69a2e7951ba08190960e90823b5078f3 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2eb01261c81909280128b5ce75eff |
completed | Feb. 28, 2026, 1:17 p.m. |
| PD | Predicate disambiguation | batch_69a2e9530c98819085025efe4e04aa7e |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.