Triple
T5376860
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coup of 22 Floréal Year VI |
E112980
|
entity |
| Predicate | typeOfInterference |
P41951
|
FINISHED |
| Object | electoral manipulation |
—
|
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: electoral manipulation | Statement: [Coup of 22 Floréal Year VI, typeOfInterference, electoral manipulation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfInterference Context triple: [Coup of 22 Floréal Year VI, typeOfInterference, electoral manipulation]
-
A.
targetsNoiseType
Indicates that an entity is directed at, designed for, or specifically affects a particular type or category of noise.
-
B.
interventionType
chosen
Indicates the specific kind or category of action, treatment, or measure applied in an intervention.
-
C.
interferenceManagement
Indicates the management or mitigation of disruptive effects one entity’s signals or actions have on another’s performance or operation.
-
D.
conflictType
Indicates the specific kind or category of conflict that characterizes the relationship or interaction between entities.
-
E.
typeOfFaulting
Indicates the kind or classification of geological faulting that characterizes the relationship between rock units or structures.
- 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_69bd4436a1988190af18dcff7fd306b4 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd88801b188190b9ac35ed89167fa3 |
completed | March 20, 2026, 5:48 p.m. |
| PD | Predicate disambiguation | batch_69bd846172788190969f24bc7503c05e |
completed | March 20, 2026, 5:31 p.m. |
Created at: March 20, 2026, 2:03 p.m.