Triple
T19015719
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | François Barthélemy |
E465342
|
entity |
| Predicate | wasAmnestied |
P134133
|
FINISHED |
| Object | 1799 |
—
|
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: 1799 | Statement: [François Barthélemy, wasAmnestied, 1799]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wasAmnestied Context triple: [François Barthélemy, wasAmnestied, 1799]
-
A.
typeOfAmnesty
Indicates the specific category or kind of amnesty that applies in a given legal or political context.
-
B.
excludedFromAmnesty
Indicates that an entity is not eligible for, or is specifically denied, the benefits or protections granted by an amnesty.
-
C.
typeOfClemency
Indicates the specific kind or category of clemency granted in a clemency-related action or decision.
-
D.
conditionForAmnesty
Indicates that one situation, event, or requirement serves as a prerequisite or qualifying factor for granting amnesty.
-
E.
pardonOrClemencyBy
Indicates that an authority grants a pardon or clemency to someone, forgiving or reducing their legal penalties.
- 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_69d8dd025c188190a1d81f5b4ec7e2c6 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d6db04fc819094709f223e30a526 |
completed | April 20, 2026, 7:33 a.m. |
| PD | Predicate disambiguation | batch_69e4a2fd80c081908237317a3a883e1c |
completed | April 19, 2026, 9:40 a.m. |
| PDg | Predicate description generation | batch_69e4ad8e075c8190ad561edc5e520057 |
completed | April 19, 2026, 10:25 a.m. |
Created at: April 10, 2026, 12:02 p.m.