Triple
T7248186
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Air raid on Bari |
E156528
|
entity |
| Predicate | numberOfAircraftAttacker |
P5710
|
FINISHED |
| Object | approximately 105 German bombers |
—
|
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: approximately 105 German bombers | Statement: [Air raid on Bari, numberOfAircraftAttacker, approximately 105 German bombers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfAircraftAttacker Context triple: [Air raid on Bari, numberOfAircraftAttacker, approximately 105 German bombers]
-
A.
opponentAircraft
Indicates that one aircraft is an adversary or opposing aircraft relative to another in a conflict or competitive context.
-
B.
attackingAircraftOrigin
Indicates that one entity is the place or source from which an attacking aircraft originates.
-
C.
targetedAircraft
Indicates that one entity has selected or designated an aircraft as the object of an attack, tracking, or other directed action.
-
D.
attackingForceApprox
Indicates that one entity is the approximate attacking force, in terms of size or strength, relative to another entity or context.
-
E.
numberOfPlanes
chosen
Indicates the quantity of planes associated with or involved in a given entity or situation.
- 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_69c68827b5e481908dc05e145b2c92d4 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6ea763f208190af1210cd8d2a05c9 |
completed | March 27, 2026, 8:37 p.m. |
| PD | Predicate disambiguation | batch_69c6e7666ffc81908bf643d8257e6337 |
completed | March 27, 2026, 8:24 p.m. |
Created at: March 27, 2026, 2:56 p.m.