Triple
T799839
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Virgin Atlantic |
E17103
|
entity |
| Predicate | notableRouteType |
P19187
|
FINISHED |
| Object | London–New York transatlantic route |
—
|
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: London–New York transatlantic route | Statement: [Virgin Atlantic, notableRouteType, London–New York transatlantic route]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableRouteType Context triple: [Virgin Atlantic, notableRouteType, London–New York transatlantic route]
-
A.
notableRouteFeature
Indicates that a route is associated with a distinctive or significant feature, such as a landmark, characteristic terrain, or other notable aspect along its path.
-
B.
roadType
Indicates the classification or category of a road based on its functional or physical characteristics.
-
C.
notableLocation
Indicates that a location is especially significant, prominent, or noteworthy in relation to the subject.
-
D.
notableTrain
Indicates that there is a train or rail service associated with the subject that is considered notable or significant in some way.
-
E.
notableTarget
Indicates that the subject is particularly significant, prominent, or noteworthy with respect to the specified target.
- F. None of above. chosen
Provenance (4 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_69a49378b9c48190adbf5f62e5b7aca1 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a7cb26dc8190bdd3a278b8695873 |
completed | March 1, 2026, 8:55 p.m. |
| PD | Predicate disambiguation | batch_69a4a5122a008190b0c621b7bc588d41 |
completed | March 1, 2026, 8:44 p.m. |
| PDg | Predicate description generation | batch_69a4a5bed20c81909ecc28bf42594e72 |
completed | March 1, 2026, 8:46 p.m. |
Created at: March 1, 2026, 7:38 p.m.