Triple
T4338741
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | HM Prison Maze |
E97526
|
entity |
| Predicate | prisonerPopulationType |
P5947
|
FINISHED |
| Object | adult male 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: adult male prisoners | Statement: [HM Prison Maze, prisonerPopulationType, adult male prisoners]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: prisonerPopulationType Context triple: [HM Prison Maze, prisonerPopulationType, adult male prisoners]
-
A.
prisonType
Indicates the specific category or classification of a prison associated with an entity.
-
B.
hasPrisonerPopulation
Indicates that an entity maintains or contains a population of prisoners, specifying the number or presence of incarcerated individuals associated with it.
-
C.
numberOfPrisonersApproximate
Indicates an approximate count of prisoners associated with an entity or situation, rather than an exact number.
-
D.
estimatedPrisonerCount
Indicates the estimated number of prisoners associated with a particular context, such as a location, time period, or event.
-
E.
hasPopulationType
chosen
Indicates that an entity’s population is classified according to a specific type or category (e.g., demographic, biological, or statistical grouping).
- 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_69b3454662a481908fbcd0bbfaa3a0a4 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3516dffb48190878f81ffe71a5e82 |
completed | March 12, 2026, 11:51 p.m. |
| PD | Predicate disambiguation | batch_69b34f4fe1c481908d6d66e15697c04b |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:14 p.m.