Triple
T35054531
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Étienne Marcel |
E1011423
|
entity |
| Predicate | endCauseOfCareer |
P182058
|
FINISHED |
| Object | assassination at the Saint-Antoine gate in Paris |
—
|
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: assassination at the Saint-Antoine gate in Paris | Statement: [Étienne Marcel, endCauseOfCareer, assassination at the Saint-Antoine gate in Paris]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: endCauseOfCareer Context triple: [Étienne Marcel, endCauseOfCareer, assassination at the Saint-Antoine gate in Paris]
-
A.
managedCareerOf
Indicates that one entity was responsible for overseeing, directing, or handling the professional career of another entity.
-
B.
publicCareer
Indicates that an entity has held or pursued a role or occupation in the public sphere, such as government, politics, or other publicly visible service.
-
C.
settingOfCareer
Indicates the primary environment, context, or domain in which a person’s career takes place or is situated.
-
D.
targetCareer
Indicates that one entity is the intended or pursued career or professional goal of another entity.
-
E.
collegeCareerEnd
Indicates the point or event at which an individual's college-level athletic or academic career concludes.
- 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_69f76dd09c308190a523454853ce842b |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f7865578d48190bf90e470634fd97d |
completed | May 3, 2026, 5:31 p.m. |
| PD | Predicate disambiguation | batch_69f7841812f081909d878955d114088e |
completed | May 3, 2026, 5:21 p.m. |
| PDg | Predicate description generation | batch_69f78575917481909a3defd6a4c366bd |
completed | May 3, 2026, 5:27 p.m. |
Created at: May 3, 2026, 4:01 p.m.