Triple
T36623276
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brixton Prison |
E904100
|
entity |
| Predicate | hasPrisonTypeHistory |
P204969
|
FINISHED |
| Object | women's prison |
—
|
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: women's prison | Statement: [Brixton Prison, hasPrisonTypeHistory, women's prison]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPrisonTypeHistory Context triple: [Brixton Prison, hasPrisonTypeHistory, women's prison]
-
A.
hasFormerInmate
Indicates that an entity previously housed or supervised an individual who was once an inmate there.
-
B.
hasPrison
Indicates that one entity possesses, contains, or is the location of a prison associated with another entity.
-
C.
hasBeenImprisoned
Indicates that an entity has been confined or incarcerated in a prison or similar detention facility at some point in time.
-
D.
hasPrisonService
Indicates that an entity provides, manages, or is responsible for prison-related services or operations for another entity.
-
E.
hasHadCriminalConviction
Indicates that an entity has previously been found guilty of a criminal offense through a legal process.
- 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_69f76e6ae750819096911e6e2d4d12c5 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a037cad051c8190b28b354b89208574 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a037a0bf4b88190bdcfae9a14b51f0a |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c82f8c88190bd77a086023ac0e1 |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:11 p.m.