Triple
T32645596
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Jungle Book (TV series) |
E834587
|
entity |
| Predicate | hasMentorCharacter |
P106997
|
FINISHED |
| Object | Baloo |
—
|
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: Baloo | Statement: [The Jungle Book (TV series), hasMentorCharacter, Baloo]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMentorCharacter Context triple: [The Jungle Book (TV series), hasMentorCharacter, Baloo]
-
A.
hasMentorNickname
Indicates that one entity is known by or uses a specific nickname given or used by their mentor.
-
B.
hasMentorFullName
Indicates that an entity has a mentor whose full name is specified by the associated value.
-
C.
hasCoachCharacter
Indicates that one entity serves as the coach or trainer character associated with another entity.
-
D.
mentorCharacter
chosen
Indicates that one character serves as a mentor, providing guidance, teaching, or support to another character.
-
E.
hasMonkCharacter
Indicates that an entity includes or features a character whose role or identity is that of a monk.
- 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_69f3492e773c81908afc10651e46cad3 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fe9dfaa2d08190b2084f63f842eb6b |
completed | May 9, 2026, 2:37 a.m. |
| PD | Predicate disambiguation | batch_69fe9bba947c81908b0b2b92a4d19b37 |
completed | May 9, 2026, 2:28 a.m. |
Created at: May 1, 2026, 1:07 a.m.