Triple
T15178533
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | L’Oblat |
E362675
|
entity |
| Predicate | hasRecurringProtagonist |
P75055
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [L’Oblat, hasRecurringProtagonist, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRecurringProtagonist Context triple: [L’Oblat, hasRecurringProtagonist, true]
-
A.
hasRecurringProtagonists
chosen
Indicates that the same main character or set of main characters appears repeatedly across multiple works or installments in a series.
-
B.
hasRecurringSeriesProtagonists
Indicates that a recurring series features one or more protagonists who appear repeatedly across its installments.
-
C.
usesRecurringProtagonistName
Indicates that a work repeatedly features the same protagonist character under a consistent name across multiple installments or stories.
-
D.
hasProtagonist
Indicates that a work of narrative has a main character who serves as its central focus or driving agent.
-
E.
protagonistIs
Indicates that one entity serves as the main character or central figure in relation to another entity or narrative context.
- 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_69d85a09a39c81908759f23268e2d408 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e00663b4148190b647592eda315d1d |
completed | April 15, 2026, 9:42 p.m. |
| PD | Predicate disambiguation | batch_69deb97bd8bc8190b2ad4888f97cf963 |
completed | April 14, 2026, 10:02 p.m. |
Created at: April 10, 2026, 3:09 a.m.