Triple
T29200346
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John the Fearless |
E740250
|
entity |
| Predicate | orderedAssassinationOf |
P104597
|
FINISHED |
| Object | Louis I, Duke of Orléans |
—
|
NE NERFINISHED |
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: Louis I, Duke of Orléans | Statement: [John the Fearless, orderedAssassinationOf, Louis I, Duke of Orléans]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: orderedAssassinationOf Context triple: [John the Fearless, orderedAssassinationOf, Louis I, Duke of Orléans]
-
A.
ordersAssassinationOf
chosen
Indicates that one entity commands or arranges for another entity to be killed, typically through a hired or subordinate agent.
-
B.
assassinationEvent
Indicates a deliberate killing of a specific individual, typically for political or strategic reasons, carried out as a planned event.
-
C.
relatedAssassination
Indicates a relationship where one entity is connected to, involved in, or associated with an assassination event concerning another entity.
-
D.
assassinatedIn
Indicates that an assassination of one entity occurred within the specified location or context represented by another entity.
-
E.
assassinated
Indicates that one entity deliberately killed another, typically for political, ideological, or strategic reasons.
- 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_69f07cb974108190b7e86ca489a6ebb6 |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_69f6afebd7ec8190ab696f363d84abf0 |
completed | May 3, 2026, 2:16 a.m. |
| PD | Predicate disambiguation | batch_69f6aca204148190850a3dc325bc07b7 |
completed | May 3, 2026, 2:02 a.m. |
Created at: April 28, 2026, 12:06 p.m.