Triple
T29091576
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Scooter Libby |
E734865
|
entity |
| Predicate | penaltyStatus |
P166544
|
FINISHED |
| Object | prison sentence commuted |
—
|
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 sentence commuted | Statement: [Scooter Libby, penaltyStatus, prison sentence commuted]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: penaltyStatus Context triple: [Scooter Libby, penaltyStatus, prison sentence commuted]
-
A.
penaltyAppliesTo
Indicates that a specific penalty is imposed on, or is relevant to, a particular entity or situation.
-
B.
penaltyPoints
Indicates that a certain number of negative points or demerits are assigned to an entity as a consequence of a rule violation, error, or infraction.
-
C.
penaltyProvision
Indicates that a rule, contract, or law includes a clause specifying a punishment or sanction for non-compliance or violation.
-
D.
penaltyOrder
Indicates that an authority has issued a formal decision imposing a penalty or sanction on a party.
-
E.
supportsPenalty
Indicates that one entity endorses, approves of, or is in favor of a particular penalty being applied to another entity or situation.
- 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_69f05b0ed66481908f2e864fa550d2f1 |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69f6622808b48190bbabcc75288ab031 |
completed | May 2, 2026, 8:44 p.m. |
| PD | Predicate disambiguation | batch_69f660f082508190a95a7888ad66cb2e |
completed | May 2, 2026, 8:39 p.m. |
| PDg | Predicate description generation | batch_69f6617a7e7c81908cfac4a2250797ee |
completed | May 2, 2026, 8:41 p.m. |
Created at: April 28, 2026, 11:05 a.m.