Triple
T27672909
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Operation Medusa |
E697705
|
entity |
| Predicate | CanadianFatalities |
P94437
|
FINISHED |
| Object | over a dozen Canadian soldiers killed |
—
|
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 a dozen Canadian soldiers killed | Statement: [Operation Medusa, CanadianFatalities, over a dozen Canadian soldiers killed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: CanadianFatalities Context triple: [Operation Medusa, CanadianFatalities, over a dozen Canadian soldiers killed]
-
A.
CanadianCasualtiesApprox
chosen
Indicates an approximate number or estimate of Canadian casualties resulting from a particular event or situation.
-
B.
causedFatalities
Indicates that the referenced event or action directly resulted in one or more deaths.
-
C.
fatalitiesCategory
Indicates the classification of deaths associated with an event, incident, or condition into a specific category or severity level.
-
D.
deathToll
Indicates the number of deaths resulting from a particular event, situation, or cause.
-
E.
constructionAccidentFatalities
Indicates that a construction-related accident resulted in one or more fatalities.
- 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_69ef590d458c81909583290c3cd0478b |
completed | April 27, 2026, 12:39 p.m. |
| NER | Named-entity recognition | batch_69f6353119a48190a5f4578d7e446c07 |
completed | May 2, 2026, 5:32 p.m. |
| PD | Predicate disambiguation | batch_69f62c1a92648190835a2c5250d8c758 |
completed | May 2, 2026, 4:53 p.m. |
Created at: April 27, 2026, 2:42 p.m.