Triple
T1505214
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nestor Makhno |
E33883
|
entity |
| Predicate | imprisonmentReason |
P3353
|
FINISHED |
| Object | revolutionary activities |
—
|
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: revolutionary activities | Statement: [Nestor Makhno, imprisonmentReason, revolutionary activities]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: imprisonmentReason Context triple: [Nestor Makhno, imprisonmentReason, revolutionary activities]
-
A.
imprisonedFor
chosen
Indicates that one entity is held in detention or jail as a consequence of, or in connection with, a specific reason, action, or offense committed by another entity or itself.
-
B.
imprisonmentContext
Indicates that one entity is held in confinement or custody by another entity or authority within a specific legal, temporal, or situational context.
-
C.
durationOfImprisonment
Indicates the length of time that an entity is or was held in imprisonment.
-
D.
hasBeenImprisonedBy
Indicates that one entity has been confined or incarcerated under the authority or control of another entity.
-
E.
usedForImprisoning
Indicates that something serves as a means, tool, or method for confining or detaining someone against their will.
- 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_69a885f352a4819099b24ff15489dede |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a90584b8b881908e112c7e59163812 |
completed | March 5, 2026, 4:24 a.m. |
| PD | Predicate disambiguation | batch_69a88727ce48819089b482cdc25453d1 |
completed | March 4, 2026, 7:25 p.m. |
Created at: March 4, 2026, 7:24 p.m.