Triple
T35305674
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Julie d’Aiglemont |
E1019628
|
entity |
| Predicate | characterInCycle |
P141621
|
FINISHED |
| Object | La Comédie humaine |
—
|
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: La Comédie humaine | Statement: [Julie d’Aiglemont, characterInCycle, La Comédie humaine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterInCycle Context triple: [Julie d’Aiglemont, characterInCycle, La Comédie humaine]
-
A.
cycleCharacter
Indicates that one character in a sequence is followed by another in a repeating (cyclic) order.
-
B.
isRecurringCharacter
chosen
Indicates that an entity appears repeatedly or regularly within a given narrative, series, or context rather than only once.
-
C.
cycleMainCharacter
Indicates that an entity serves as the primary or central character within a particular cycle, sequence, or recurring narrative.
-
D.
characterIn
Indicates that an entity appears as a character within a specified work, story, or narrative.
-
E.
hasRecurringCharacterFrom
Indicates that one work or series includes a character who also appears recurrently in another work or series.
- 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_69f76de8b4c48190ae504b86185c474c |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69ff956dc6548190979171d4b4068d47 |
completed | May 9, 2026, 8:13 p.m. |
| PD | Predicate disambiguation | batch_69ff93dc39c481908a97a12c3ef7dfe7 |
completed | May 9, 2026, 8:06 p.m. |
Created at: May 3, 2026, 4:03 p.m.