Triple
T352016
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Operation Chastise |
E7462
|
entity |
| Predicate | RAFcasualties |
P1399
|
FINISHED |
| Object | loss of several attacking aircraft |
—
|
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: loss of several attacking aircraft | Statement: [Operation Chastise, RAFcasualties, loss of several attacking aircraft]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: RAFcasualties Context triple: [Operation Chastise, RAFcasualties, loss of several attacking aircraft]
-
A.
commanderOfRAF
Indicates that one entity serves as the commander or head of the Royal Air Force in relation to another entity.
-
B.
NATOcasualtiesMilitaryKilled
Indicates that members of NATO military forces were killed as casualties.
-
C.
casualtiesBritishWounded
Indicates the number of British individuals who were wounded as a result of a specific event or action.
-
D.
casualties
chosen
Indicates that an event, action, or situation resulted in people being killed or injured.
-
E.
militaryCasualtiesEstimate
Indicates an estimated number of people killed, wounded, or missing as a result of military conflict or operations.
- 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_69a2e7e696948190bebc966535995e45 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2eb7f1be88190964ddcbb6a05f021 |
completed | Feb. 28, 2026, 1:19 p.m. |
| PD | Predicate disambiguation | batch_69a2e9571bd88190b6fcb16f21604720 |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.