Triple
T27428060
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | René-François Dumas |
E690545
|
entity |
| Predicate | wasArrestedAfter |
P162401
|
FINISHED |
| Object | fall of Robespierre |
—
|
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: fall of Robespierre | Statement: [René-François Dumas, wasArrestedAfter, fall of Robespierre]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wasArrestedAfter Context triple: [René-François Dumas, wasArrestedAfter, fall of Robespierre]
-
A.
wasArrested
Indicates that an authority detained and took a person into legal custody in connection with a suspected offense.
-
B.
wasArrestedDuring
Indicates that an entity was arrested in the course of, or at the time of, a specified event or activity.
-
C.
hasBeenArrestedBy
Indicates that an entity has been taken into custody or formally apprehended by another entity, typically a law enforcement authority.
-
D.
arrestedFor
Indicates that an authority has taken someone into custody because they are suspected or accused of committing a specified offense or wrongdoing.
-
E.
hasReasonForArrest
Indicates that an arrest is associated with a specific reason or cause.
- 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_69ef52003fb48190b0f1295246182a86 |
completed | April 27, 2026, 12:09 p.m. |
| NER | Named-entity recognition | batch_69f62d570d548190b7f696646baee862 |
completed | May 2, 2026, 4:59 p.m. |
| PD | Predicate disambiguation | batch_69f623aaf40081909f947431424a1d55 |
completed | May 2, 2026, 4:17 p.m. |
| PDg | Predicate description generation | batch_69f624c006788190a2f4d5015c96463f |
completed | May 2, 2026, 4:22 p.m. |
Created at: April 27, 2026, 12:41 p.m.