Triple
T7160665
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AY |
E166932
|
entity |
| Predicate | airlineLongHaulFocus |
P5534
|
FINISHED |
| Object | Asia-Europe 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: Asia-Europe routes | Statement: [AY, airlineLongHaulFocus, Asia-Europe routes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: airlineLongHaulFocus Context triple: [AY, airlineLongHaulFocus, Asia-Europe routes]
-
A.
mainAirlineFocus
Indicates that an airline is the primary or central focus of attention, operations, or analysis in a given context.
-
B.
hasLongHaulFlights
chosen
Indicates that an entity (such as an airline, route, or airport) operates or is associated with long-distance flights typically covering intercontinental or extended-duration journeys.
-
C.
airlineType
Indicates the classification or category of an airline based on its operational or service characteristics.
-
D.
operatesLongHaulRouteFrom
Indicates that an entity (typically a transportation carrier) runs long-distance routes originating from a specified location.
-
E.
airlinesUse
Indicates that certain airlines operate, employ, or make use of a specified resource, service, or system.
- 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_69c68887a5cc8190bec0ea96227164f7 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e82ce770819081dccf7ffd50c2ab |
completed | March 27, 2026, 8:27 p.m. |
| PD | Predicate disambiguation | batch_69c6e1cd5c948190a9113b23f7308c21 |
completed | March 27, 2026, 8 p.m. |
Created at: March 27, 2026, 2:47 p.m.