Triple
T30997613
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Coquille et le Clergyman |
E789847
|
entity |
| Predicate | scenarioBy |
P1955
|
FINISHED |
| Object | Antonin Artaud |
—
|
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: Antonin Artaud | Statement: [La Coquille et le Clergyman, scenarioBy, Antonin Artaud]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scenarioBy Context triple: [La Coquille et le Clergyman, scenarioBy, Antonin Artaud]
-
A.
scenarioType
Indicates the specific category or kind of situation, context, or use case that an entity or event is associated with.
-
B.
variantScenario
Indicates a scenario that represents an alternative, modified, or derived version of another base scenario.
-
C.
narrativeSituation
Indicates the contextual relationship that defines how events, characters, and perspectives are arranged and presented within a narrative.
-
D.
scenes
Indicates that one entity is a scene or setting in which the other entity occurs, appears, or is depicted.
-
E.
storyBy
chosen
Indicates that one entity is the creator or author of the story associated with another entity.
- F. None of above.
Provenance (3 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_69f224c65a348190baaed1c01a29900c |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f6953bafb88190a860e9c68a3dd4b2 |
completed | May 3, 2026, 12:22 a.m. |
| PD | Predicate disambiguation | batch_69f690ef92308190903a54fc74233269 |
completed | May 3, 2026, 12:03 a.m. |
Created at: April 29, 2026, 8:56 p.m.