Triple
T25597608
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aaron McKinney |
E641695
|
entity |
| Predicate | avoidedPenalty |
P129050
|
FINISHED |
| Object | death penalty |
—
|
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: death penalty | Statement: [Aaron McKinney, avoidedPenalty, death penalty]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: avoidedPenalty Context triple: [Aaron McKinney, avoidedPenalty, death penalty]
-
A.
avoidedFor
Indicates that one entity is deliberately not used, chosen, or engaged with because of the presence, influence, or characteristics of another entity.
-
B.
avoidedConsequence
Indicates that an action or event prevented a particular consequence from occurring.
-
C.
defaultPenalty
Indicates that a standard or automatically applied penalty is imposed in the absence of a specific or overridden penalty.
-
D.
legalConsequenceAvoided
chosen
Indicates that an action, decision, or circumstance resulted in preventing or escaping an otherwise applicable legal penalty, liability, or sanction.
-
E.
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.
- 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_69e75dc60d108190b7e2419e36b0134b |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f5f9a420f08190a8ed8c9a8c245fc4 |
completed | May 2, 2026, 1:18 p.m. |
| PD | Predicate disambiguation | batch_69f480789be08190ab252a6de3797200 |
completed | May 1, 2026, 10:29 a.m. |
Created at: April 21, 2026, 4:28 p.m.