Triple
T29432516
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hussein Dey |
E746471
|
entity |
| Predicate | consequenceOfFlyWhiskIncident |
P150475
|
FINISHED |
| Object | used as pretext by France for invasion of Algiers |
—
|
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: used as pretext by France for invasion of Algiers | Statement: [Hussein Dey, consequenceOfFlyWhiskIncident, used as pretext by France for invasion of Algiers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: consequenceOfFlyWhiskIncident Context triple: [Hussein Dey, consequenceOfFlyWhiskIncident, used as pretext by France for invasion of Algiers]
-
A.
flyWhiskIncidentRole
Indicates the role an entity plays in an incident involving a fly whisk (e.g., user, target, or other participant in the event).
-
B.
fliesOnOccasion
Indicates that an entity sometimes engages in flying, but not regularly or continuously.
-
C.
consequenceOfFalling
Indicates that something occurs as a result or outcome of a falling event.
-
D.
unexpectedConsequenceOf
chosen
Indicates that one event, action, or condition occurs as an unforeseen or unintended result of another.
-
E.
fliesOn
Indicates that an entity travels as a passenger or cargo aboard a particular aircraft, airline, or flight.
- 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_69f0a7a06e0081908add494075912eb4 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69f6d0d46aec819091edf97324d793ac |
completed | May 3, 2026, 4:36 a.m. |
| PD | Predicate disambiguation | batch_69f6cfe2183481908ae4e85a59c66f69 |
completed | May 3, 2026, 4:32 a.m. |
Created at: April 28, 2026, 3:14 p.m.