Triple
T20141315
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Old Man |
E491171
|
entity |
| Predicate | bearerImprisonment |
P104435
|
FINISHED |
| Object | federal prison sentence in the 1970s |
—
|
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: federal prison sentence in the 1970s | Statement: [The Old Man, bearerImprisonment, federal prison sentence in the 1970s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bearerImprisonment Context triple: [The Old Man, bearerImprisonment, federal prison sentence in the 1970s]
-
A.
imprisonedFor
Indicates that one entity is held in detention or jail as a consequence of, or in connection with, a specific reason, action, or offense committed by another entity or itself.
-
B.
imprisonedWith
Indicates that two entities are confined or held in prison together at the same time and place.
-
C.
hasBeenImprisoned
chosen
Indicates that an entity has been confined or incarcerated in a prison or similar detention facility at some point in time.
-
D.
usedForImprisoning
Indicates that something serves as a means, tool, or method for confining or detaining someone against their will.
-
E.
sometimesImprisons
Indicates that one entity occasionally confines or incarcerates another entity, but not on a regular or constant basis.
- 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_69da6265f8f0819080b29c752a574088 |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e6679b179c8190a9511df8ed82098a |
completed | April 20, 2026, 5:51 p.m. |
| PD | Predicate disambiguation | batch_69e54cfb0d0081908e789b9b57e96668 |
completed | April 19, 2026, 9:45 p.m. |
Created at: April 11, 2026, 11:32 p.m.