Triple
T19818605
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charles-Henri Sanson |
E476124
|
entity |
| Predicate | numberOfYearsAsChiefExecutioner |
P137437
|
FINISHED |
| Object | approximately 40 |
—
|
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: approximately 40 | Statement: [Charles-Henri Sanson, numberOfYearsAsChiefExecutioner, approximately 40]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfYearsAsChiefExecutioner Context triple: [Charles-Henri Sanson, numberOfYearsAsChiefExecutioner, approximately 40]
-
A.
numberOfPeopleExecuted
Indicates the total count of individuals who were put to death, typically as a result of a formal execution process.
-
B.
hasNotablePersonExecuted
Indicates that a notable or prominent person has been subjected to execution (e.g., capital punishment) in relation to the referenced entity.
-
C.
executionPeriodByElectricChair
Indicates that an execution took place during a specified time period using the electric chair as the method.
-
D.
primaryPerpetratorExecutionDate
Indicates the date on which the main perpetrator of an act or crime was executed.
-
E.
timeInOfficeBeforeAssassination
Indicates the duration an individual held office prior to being assassinated.
- 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_69d8e51bc4208190a1c57d8c5d1b15e4 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e654fc8b94819095fd5240f33b6713 |
completed | April 20, 2026, 4:31 p.m. |
| PD | Predicate disambiguation | batch_69e5305858108190bbbfdb9ba3ab9f80 |
completed | April 19, 2026, 7:43 p.m. |
| PDg | Predicate description generation | batch_69e532bcf41c8190b685b5adf46a60fc |
completed | April 19, 2026, 7:53 p.m. |
Created at: April 10, 2026, 1:50 p.m.