Triple
T5018612
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Litchfield Penitentiary |
E112794
|
entity |
| Predicate | hasFictionalProgram |
P57670
|
FINISHED |
| Object | prison labor program |
—
|
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: prison labor program | Statement: [Litchfield Penitentiary, hasFictionalProgram, prison labor program]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalProgram Context triple: [Litchfield Penitentiary, hasFictionalProgram, prison labor program]
-
A.
hasFictionalShowWithinShow
Indicates that one show contains or features another fictional show within its narrative.
-
B.
hasFictionalWork
Indicates that one entity is the creator, owner, or source of a fictional work associated with another entity.
-
C.
featuresFictionalProgram
chosen
Indicates that a work includes or presents a fictional program (such as a TV show, software, or in-universe broadcast) as part of its content.
-
D.
hasFictionalRole
Indicates that an entity plays or is assigned a specific role within a fictional work or narrative.
-
E.
hasFictionalProperty
Indicates that an entity possesses a property, attribute, or characteristic that exists only in a fictional or imaginary context.
- 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_69bd4435c2f48190be593158cbfcf8a3 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd73415e088190802f9bb283262386 |
completed | March 20, 2026, 4:18 p.m. |
| PD | Predicate disambiguation | batch_69bd714ecfe08190b5830cfc1c74fa17 |
completed | March 20, 2026, 4:09 p.m. |
Created at: March 20, 2026, 1:35 p.m.