Triple
T29997944
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ford Grey, 1st Earl of Tankerville |
E762080
|
entity |
| Predicate | wasPardoned |
P134133
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Ford Grey, 1st Earl of Tankerville, wasPardoned, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wasPardoned Context triple: [Ford Grey, 1st Earl of Tankerville, wasPardoned, true]
-
A.
wasAmnestied
chosen
Indicates that an entity was officially granted amnesty, nullifying or forgiving prior offenses or penalties.
-
B.
pardonOrClemencyBy
Indicates that an authority grants a pardon or clemency to someone, forgiving or reducing their legal penalties.
-
C.
posthumousPardonGrantedBy
Indicates that a formal pardon was granted to an individual after their death by a specified authority or institution.
-
D.
typeOfClemency
Indicates the specific kind or category of clemency granted in a clemency-related action or decision.
-
E.
clemencyPower
Indicates the authority to grant mercy or reduce or cancel penalties imposed on others.
- 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_69f224695498819094a81037cad401e2 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f6794c44c881908db0716b99c32481 |
completed | May 2, 2026, 10:23 p.m. |
| PD | Predicate disambiguation | batch_69f66ec9919881908a187bfc7c4df192 |
completed | May 2, 2026, 9:38 p.m. |
Created at: April 29, 2026, 6:40 p.m.