Triple
T8243310
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cold Mountain Penitentiary |
E192787
|
entity |
| Predicate | hasInmateSpecies |
P57303
|
FINISHED |
| Object | human |
—
|
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: human | Statement: [Cold Mountain Penitentiary, hasInmateSpecies, human]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInmateSpecies Context triple: [Cold Mountain Penitentiary, hasInmateSpecies, human]
-
A.
hasPrisoners
chosen
Indicates that an entity holds or contains one or more individuals who are imprisoned or detained.
-
B.
memberSpecies
Indicates that a particular species is a constituent or member of a larger biological or taxonomic group.
-
C.
hasPrison
Indicates that one entity possesses, contains, or is the location of a prison associated with another entity.
-
D.
hasPrisonerCategory
Indicates the classification or category assigned to a prisoner within a correctional or detention system.
-
E.
hasLargeSpecies
Indicates that an entity possesses or includes at least one species that is considered large in size.
- 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_69ca82de7b8c81908d8106f8a53cff9b |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb786f65708190a92ec282b280c813 |
completed | March 31, 2026, 7:31 a.m. |
| PD | Predicate disambiguation | batch_69cb36b437e881909958591357e83b9d |
completed | March 31, 2026, 2:51 a.m. |
Created at: March 30, 2026, 5:47 p.m.