Triple
T14119328
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peter and the Wolf |
E339863
|
entity |
| Predicate | characterRepresentation |
P112886
|
FINISHED |
| Object | Cat |
E1080528
|
NE 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: Cat | Statement: [Peter and the Wolf, characterRepresentation, Cat]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cat Context triple: [Peter and the Wolf, characterRepresentation, Cat]
-
A.
Cat
Cat is a feline character in Maurice Ravel’s opera "L’enfant et les sortilèges," known for its expressive, anthropomorphic role in the magical, surreal narrative.
-
B.
the Cat
chosen
The Cat is a sly, cautious feline character in Sergei Prokofiev’s musical fairy tale "Peter and the Wolf," represented by the clarinet in the orchestra.
-
C.
Cats
Cats is a long-running, award-winning musical composed by Andrew Lloyd Webber, based on T.S. Eliot’s "Old Possum’s Book of Practical Cats," renowned for its distinctive costumes, choreography, and songs like "Memory."
-
D.
Cats
Cats is the informal nickname commonly used to refer to the University of Arizona’s athletic teams, the Arizona Wildcats.
-
E.
CAT
CAT is a globally recognized industrial brand best known for its heavy construction machinery, engines, and rugged workwear.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcdf0641008190b88efacc02ba5314 |
completed | May 7, 2026, 6:50 p.m. |
Created at: April 9, 2026, 10:22 p.m.