Triple
T32345837
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cimetière de Picpus |
E826456
|
entity |
| Predicate | victimsExecutedAt |
P174172
|
FINISHED |
| Object | Place du Trône-Renversé |
—
|
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: Place du Trône-Renversé | Statement: [Cimetière de Picpus, victimsExecutedAt, Place du Trône-Renversé]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: victimsExecutedAt Context triple: [Cimetière de Picpus, victimsExecutedAt, Place du Trône-Renversé]
-
A.
killingDate
Indicates the specific date on which a killing event occurred.
-
B.
primaryPerpetratorExecutionDate
Indicates the date on which the main perpetrator of an act or crime was executed.
-
C.
assassinationDate
Indicates the date on which an assassination of the referenced entity occurred.
-
D.
victimOfExecutionBy
Indicates that one entity was executed as a result of an execution carried out by another entity.
-
E.
numberOfPeopleExecuted
Indicates the total count of individuals who were put to death, typically as a result of a formal execution process.
- 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_69f34914dfc48190a390cd0720d9e86f |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6be5165a88190b7ca9133e827087e |
completed | May 3, 2026, 3:17 a.m. |
| PD | Predicate disambiguation | batch_69f6ba6cef208190bc5cd43d96127004 |
completed | May 3, 2026, 3:01 a.m. |
| PDg | Predicate description generation | batch_69f6bbbe23d48190b2aa662d69b41900 |
completed | May 3, 2026, 3:06 a.m. |
Created at: May 1, 2026, 12:48 a.m.