Triple
T27354454
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TaleSpin |
E685645
|
entity |
| Predicate | reimaginesCharactersFrom |
P78725
|
FINISHED |
| Object | The Jungle Book (1967 film) |
—
|
NE NERFINISHED |
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: The Jungle Book (1967 film) | Statement: [TaleSpin, reimaginesCharactersFrom, The Jungle Book (1967 film)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reimaginesCharactersFrom Context triple: [TaleSpin, reimaginesCharactersFrom, The Jungle Book (1967 film)]
-
A.
inspiredRemakeCharacter
Indicates that one character in a remake is based on, modeled after, or creatively derived from another character in an earlier work.
-
B.
reimagines
chosen
Indicates that one entity creatively reconceives, interprets, or presents another in a significantly new or different way.
-
C.
partOfReimaginingOf
Indicates that something is a component or segment within a larger work that is itself a reimagined version of an earlier work.
-
D.
adaptationOfCharacterFrom
Indicates that one character is derived, modified, or reinterpreted from an existing character in another work or version.
-
E.
filmCharacterVersionOf
Indicates that one character is a specific film adaptation or portrayal of another character originating from a different version or medium.
- 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_69ef14887c288190931b8431fdbf53c4 |
completed | April 27, 2026, 7:47 a.m. |
| NER | Named-entity recognition | batch_69f62c1c72f08190b50b81c56e59da63 |
completed | May 2, 2026, 4:53 p.m. |
| PD | Predicate disambiguation | batch_69f620e4b1c88190a17940251abc68fd |
completed | May 2, 2026, 4:05 p.m. |
Created at: April 27, 2026, 11:50 a.m.