Triple
T32596504
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jean-Marie Bastien-Thiry |
E833223
|
entity |
| Predicate | pardonDecisionBy |
P174930
|
FINISHED |
| Object | Charles de Gaulle |
—
|
NE NERFINISHED |
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: Charles de Gaulle | Statement: [Jean-Marie Bastien-Thiry, pardonDecisionBy, Charles de Gaulle]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: pardonDecisionBy Context triple: [Jean-Marie Bastien-Thiry, pardonDecisionBy, Charles de Gaulle]
-
A.
pardonStatus
Indicates whether an entity has been officially forgiven or exempted from penalties for a prior offense or violation.
-
B.
pardonReason
Indicates the reason or justification for which a pardon is granted.
-
C.
pardonDate
Indicates the date on which an official pardon for an offense is granted or takes effect.
-
D.
pardonJurisdiction
Indicates the authority or legal power an entity has to grant pardons for offenses within a particular scope or jurisdiction.
-
E.
pardonReceivedFrom
Indicates that one entity has been officially forgiven or had penalties removed by another authority or individual.
- 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_69f3492ab63c8190aec24d5003b47c29 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6c90790788190a1ed09adc86ed22d |
completed | May 3, 2026, 4:03 a.m. |
| PD | Predicate disambiguation | batch_69f6c3f42fbc8190a06eb1044c9e6094 |
completed | May 3, 2026, 3:41 a.m. |
| PDg | Predicate description generation | batch_69f6c814c26c81908f5c47285129ff2a |
completed | May 3, 2026, 3:59 a.m. |
Created at: May 1, 2026, 1:05 a.m.