Triple
T35529750
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Operation Unified Protector |
E1026765
|
entity |
| Predicate | airSortiesFlown |
P106643
|
FINISHED |
| Object | over 26,000 |
—
|
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: over 26,000 | Statement: [Operation Unified Protector, airSortiesFlown, over 26,000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: airSortiesFlown Context triple: [Operation Unified Protector, airSortiesFlown, over 26,000]
-
A.
hasFlownSorties
chosen
Indicates that an entity has completed one or more operational flight missions (sorties).
-
B.
aircraftFlown
Indicates that an entity (typically a person or organization) operates or pilots a particular aircraft.
-
C.
numberOfAerialVictories
Indicates the count of successful aerial combat victories achieved by an entity over opposing aircraft.
-
D.
dailySorties
Indicates the number of missions or operations carried out per day by an entity.
-
E.
estimatedAerialVictories
Indicates an approximate count of aerial combat victories attributed to an entity, rather than an exact, confirmed total.
- 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_69f76dff7e508190b28ceeee770dce23 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f79a54aa3c8190b2bb5d790b2d42d4 |
completed | May 3, 2026, 6:56 p.m. |
| PD | Predicate disambiguation | batch_69f7961970408190b669cc556e30a608 |
completed | May 3, 2026, 6:38 p.m. |
Created at: May 3, 2026, 4:04 p.m.