Triple
T3467716
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Château d’If |
E73176
|
entity |
| Predicate | historicallyUsedToImprison |
P22043
|
FINISHED |
| Object | political prisoners |
—
|
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: political prisoners | Statement: [Château d’If, historicallyUsedToImprison, political prisoners]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: historicallyUsedToImprison Context triple: [Château d’If, historicallyUsedToImprison, political prisoners]
-
A.
usedForImprisoning
chosen
Indicates that something serves as a means, tool, or method for confining or detaining someone against their will.
-
B.
wasImprisonedIn
Indicates that an entity was held in confinement or incarcerated at a particular place or facility.
-
C.
imprisonedWith
Indicates that two entities are confined or held in prison together at the same time and place.
-
D.
hasBeenImprisonedBy
Indicates that one entity has been confined or incarcerated under the authority or control of another entity.
-
E.
periodOfUseAsPrison
Indicates the time span during which something functioned or was used as a prison.
- 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_69ad85b224d481908ff8be51338d24ff |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adbb11ec5881908347bf92883a25ee |
completed | March 8, 2026, 6:08 p.m. |
| PD | Predicate disambiguation | batch_69adae05bb0081909dc7e4779d6e05ef |
completed | March 8, 2026, 5:12 p.m. |
Created at: March 8, 2026, 3:17 p.m.