Triple
T14119346
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peter and the Wolf |
E339863
|
entity |
| Predicate | typicalNarrators |
P32398
|
FINISHED |
| Object | actors |
—
|
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: actors | Statement: [Peter and the Wolf, typicalNarrators, actors]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalNarrators Context triple: [Peter and the Wolf, typicalNarrators, actors]
-
A.
narratorType
chosen
Indicates the narrative perspective or role from which a story or account is being told.
-
B.
narratorOf
Indicates that one entity serves as the narrator or storytelling voice for another entity, such as a text, story, or media work.
-
C.
narratorRole
Indicates that one entity serves as the narrator of another entity (such as a story, text, or media work), specifying the narrative role or function it performs.
-
D.
fictionalNarrator
Indicates that one entity serves as the narrator or storytelling voice within a fictional work that features the other entity.
-
E.
narratesAs
Indicates that one entity tells, recounts, or presents a story, event, or information in the manner, style, or voice of 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_69d81c6a95b481909e39111e0c1f31ee |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de609322ac8190bb389ca250882af5 |
completed | April 14, 2026, 3:43 p.m. |
| PD | Predicate disambiguation | batch_69de05b2f7e481908a9a7d40153234c0 |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:22 p.m.