Triple
T26896123
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jason Marsden as Kovu (adult) |
E677902
|
entity |
| Predicate | characterFromWork |
P12208
|
FINISHED |
| Object | The Lion King II: Simba’s Pride |
—
|
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 Lion King II: Simba’s Pride | Statement: [Jason Marsden as Kovu (adult), characterFromWork, The Lion King II: Simba’s Pride]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterFromWork Context triple: [Jason Marsden as Kovu (adult), characterFromWork, The Lion King II: Simba’s Pride]
-
A.
characterInBookBy
Indicates that a character appears in a book that was written by a specified author.
-
B.
characterIn
chosen
Indicates that an entity appears as a character within a specified work, story, or narrative.
-
C.
basedOnCharacterFromWork
Indicates that one entity is derived from, inspired by, or modeled after a character that appears in another creative work.
-
D.
characterInWorkDescribedAs
Indicates that a character is portrayed or described in a particular way within a specific work.
-
E.
fictionalCharacterPortrayedFromWorkBy
Indicates that a fictional character is depicted or portrayed in a work that was created by a specific author or creator.
- 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_69eee9befee48190a26f214faa867be7 |
completed | April 27, 2026, 4:44 a.m. |
| NER | Named-entity recognition | batch_69f73ae120bc8190bff94d38d7a7a00d |
completed | May 3, 2026, 12:09 p.m. |
| PD | Predicate disambiguation | batch_69f73a38d0848190aa5139144b8561c6 |
completed | May 3, 2026, 12:06 p.m. |
Created at: April 27, 2026, 5:48 a.m.