Triple
T9996383
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | King Louie (2016 film character) |
E197211
|
entity |
| Predicate | differenceFromBook |
P74132
|
FINISHED |
| Object | does not appear in Rudyard Kipling’s original stories |
—
|
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: does not appear in Rudyard Kipling’s original stories | Statement: [King Louie (2016 film character), differenceFromBook, does not appear in Rudyard Kipling’s original stories]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: differenceFromBook Context triple: [King Louie (2016 film character), differenceFromBook, does not appear in Rudyard Kipling’s original stories]
-
A.
differenceDescription
chosen
Indicates a textual explanation that characterizes how two entities differ from each other.
-
B.
book1Contains
Indicates that one book includes, encloses, or has as part of its content another specified element or section.
-
C.
differIn
Indicates that two entities are not the same in at least one specified aspect, attribute, or value.
-
D.
partOfBook
Indicates that one entity is a component or section contained within a larger book entity.
-
E.
usesBookAs
Indicates that one entity employs or treats a book as a particular tool, resource, or role in a given context.
- 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_69ca82f3b61c81908ecc2c1c96dbc2e4 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdcb9af6a88190942cc4991bd373c1 |
completed | April 2, 2026, 1:51 a.m. |
| PD | Predicate disambiguation | batch_69cd1da07db88190945bcdab3ca82e71 |
completed | April 1, 2026, 1:29 p.m. |
Created at: March 30, 2026, 8:50 p.m.