Triple
T36906012
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ray Dehn |
E912778
|
entity |
| Predicate | receivedPardon |
P31345
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Ray Dehn, receivedPardon, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: receivedPardon Context triple: [Ray Dehn, receivedPardon, yes]
-
A.
pardonOrRelease
Indicates that an authority formally forgives an entity for an offense or frees them from custody, penalty, or imposed restrictions.
-
B.
pardonOrClemencyBy
Indicates that an authority grants a pardon or clemency to someone, forgiving or reducing their legal penalties.
-
C.
soughtPardonFor
Indicates that one entity requested or attempted to obtain a formal pardon or forgiveness for another entity or for a specific action.
-
D.
typeOfClemency
Indicates the specific kind or category of clemency granted in a clemency-related action or decision.
-
E.
pardonReceivedFrom
chosen
Indicates that one entity has been officially forgiven or had penalties removed by another authority or individual.
- 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_69f76e879768819085c2fb31a6a5b44b |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fce28d6c3081908bf76f5db63ecf68 |
completed | May 7, 2026, 7:05 p.m. |
| PD | Predicate disambiguation | batch_69fce12d2f08819082134b5eb3db6a24 |
completed | May 7, 2026, 6:59 p.m. |
Created at: May 3, 2026, 4:13 p.m.