Triple
T2917779
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frecce Tricolori |
E78647
|
entity |
| Predicate | numberOfPilotsInDisplay |
P43895
|
FINISHED |
| Object | 10 |
—
|
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: 10 | Statement: [Frecce Tricolori, numberOfPilotsInDisplay, 10]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfPilotsInDisplay Context triple: [Frecce Tricolori, numberOfPilotsInDisplay, 10]
-
A.
hasAircraftOnDisplay
Indicates that an entity exhibits or presents an aircraft as part of a display or collection.
-
B.
numberOfPlanes
Indicates the quantity of planes associated with or involved in a given entity or situation.
-
C.
crewCount
Indicates the number of crew members associated with an entity, such as a vehicle, vessel, or mission.
-
D.
replicasDisplayedIn
Indicates that replica versions of an item are presented or shown within a particular location, context, or medium.
-
E.
crewCountApproximate
Indicates that the relationship specifies an estimated or approximate number of crew members associated with an entity.
- 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_69ad8b0c2ad081909ff87050ae542bb9 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad97fd89d88190bc7db4b39058ae3a |
completed | March 8, 2026, 3:38 p.m. |
| PD | Predicate disambiguation | batch_69ad9603ddd88190b8bf91bc7517cc21 |
completed | March 8, 2026, 3:30 p.m. |
| PDg | Predicate description generation | batch_69ad97f520208190a4dc43372004555f |
completed | March 8, 2026, 3:38 p.m. |
Created at: March 8, 2026, 2:54 p.m.