Triple
T29054322
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prisons: A Social Crime and Failure |
E735346
|
entity |
| Predicate | positionOnPrisons |
P193598
|
FINISHED |
| Object | prisons are inherently unjust |
—
|
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: prisons are inherently unjust | Statement: [Prisons: A Social Crime and Failure, positionOnPrisons, prisons are inherently unjust]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: positionOnPrisons Context triple: [Prisons: A Social Crime and Failure, positionOnPrisons, prisons are inherently unjust]
-
A.
prisonLocatedIn
Indicates that a prison is situated within or at a specific geographic or administrative location.
-
B.
inmates
Indicates that one entity is confined or held as a prisoner within an institution or facility associated with another entity.
-
C.
placeOfDetention
Indicates the location or facility where an entity is or was held in detention.
-
D.
imprisonedWith
Indicates that two entities are confined or held in prison together at the same time and place.
-
E.
estimatedPrisonerCount
Indicates the estimated number of prisoners associated with a particular context, such as a location, time period, or event.
- F. None of above. chosen
Provenance (4 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_69f077e64b88819094d37bdbca8191b3 |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69fd4d1854988190be093b103a681798 |
completed | May 8, 2026, 2:40 a.m. |
| PD | Predicate disambiguation | batch_69fd4c8d1a188190897c24527337814a |
completed | May 8, 2026, 2:38 a.m. |
| PDg | Predicate description generation | batch_69fd4d16dd20819096957c40f43cd971 |
completed | May 8, 2026, 2:40 a.m. |
Created at: April 28, 2026, 10:10 a.m.