Triple
T22122890
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anne of Green Gables (1934 film) |
E546715
|
entity |
| Predicate | leadActressChangedNameAfterRole |
P147078
|
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: [Anne of Green Gables (1934 film), leadActressChangedNameAfterRole, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: leadActressChangedNameAfterRole Context triple: [Anne of Green Gables (1934 film), leadActressChangedNameAfterRole, true]
-
A.
leadActress
Indicates that the subject is the primary female performer in the specified film, show, or production.
-
B.
madeActressA
Indicates that one entity caused or was responsible for another entity becoming an actress.
-
C.
replacesInLeadRole
Indicates that one entity takes over or substitutes for another entity in the primary or leading role within a given context or production.
-
D.
actorKnownForDramaticTurn
Indicates that an actor is recognized for a notable shift from their usual roles into significantly more serious or dramatic performances.
-
E.
debutAsLeadActressYear
Indicates the year in which an entity first made her debut as a lead actress.
- 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_69e11e38b3848190ac3a4fa97d56e65a |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f1297f3fb48190b6aaca18b40c37ab |
completed | April 28, 2026, 9:41 p.m. |
| PD | Predicate disambiguation | batch_69e71b2ed7348190b6fa2e52f54393fb |
completed | April 21, 2026, 6:37 a.m. |
| PDg | Predicate description generation | batch_69e7222d208c819098b12c13e31af629 |
completed | April 21, 2026, 7:07 a.m. |
Created at: April 16, 2026, 8:31 p.m.