Triple
T30490096
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sister Bertrille |
E775833
|
entity |
| Predicate | yearsActiveInCanon |
P124244
|
FINISHED |
| Object | 1967–1970 |
—
|
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: 1967–1970 | Statement: [Sister Bertrille, yearsActiveInCanon, 1967–1970]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: yearsActiveInCanon Context triple: [Sister Bertrille, yearsActiveInCanon, 1967–1970]
-
A.
yearsActiveInStory
chosen
Indicates the span of years during which the entity is active or participates within the context of the story.
-
B.
eraInCanon
Indicates that a subject belongs to, occurs within, or is classified as part of a specific era defined in a canon or fictional continuity.
-
C.
hasPlaceInCanon
Indicates that something holds a specific status or position within an established canon or authoritative body of works.
-
D.
activeInFictionalYear
Indicates that an entity is active or operating during a specified fictional or imaginary year within a narrative or fictional timeline.
-
E.
franchiseCanonStatus
Indicates whether a work, event, or element is officially recognized as part of the established canon within a franchise.
- 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_69f22497f91c8190afa7165bc900accd |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f68748a0548190a881253cf0fd001e |
completed | May 2, 2026, 11:22 p.m. |
| PD | Predicate disambiguation | batch_69f678d2196c8190b9d0d2fcd47cc539 |
completed | May 2, 2026, 10:21 p.m. |
Created at: April 29, 2026, 8:13 p.m.