Triple
T12362913
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carmelite Prison, Paris |
E294784
|
entity |
| Predicate | notablePrisonerType |
P18550
|
FINISHED |
| Object | Catholic clergy |
—
|
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: Catholic clergy | Statement: [Carmelite Prison, Paris, notablePrisonerType, Catholic clergy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notablePrisonerType Context triple: [Carmelite Prison, Paris, notablePrisonerType, Catholic clergy]
-
A.
notablePrisoner
Indicates that a person is recognized as a significant or noteworthy inmate of a particular prison or detention facility.
-
B.
prisonerType
Indicates the classification or category assigned to a prisoner within a correctional or detention system.
-
C.
notablePrison
Indicates that an entity is a prison of particular significance or prominence in relation to another entity.
-
D.
notableArrestee
Indicates that the subject is a person who was arrested in a way considered notable or significant, typically in connection with the object (such as an event, case, or authority).
-
E.
hasNotableCategoryOfPrisoners
chosen
Indicates that a prison is known for housing a specific, notable category or type of prisoners.
- 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_69d6ab6d8a4081908636601e69ddf262 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d942a2d6e08190a13c7ff89af09354 |
completed | April 10, 2026, 6:34 p.m. |
| PD | Predicate disambiguation | batch_69d93ecf6b548190a394b6b56a0c1c68 |
completed | April 10, 2026, 6:17 p.m. |
Created at: April 8, 2026, 9:54 p.m.