Triple
T31755302
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anyone Can Cook |
E810541
|
entity |
| Predicate | inspiresCharacter |
P86314
|
FINISHED |
| Object | Remy |
—
|
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: Remy | Statement: [Anyone Can Cook, inspiresCharacter, Remy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: inspiresCharacter Context triple: [Anyone Can Cook, inspiresCharacter, Remy]
-
A.
characterInspiration
chosen
Indicates that one entity serves as the creative or conceptual inspiration for the development or portrayal of another character.
-
B.
influencesCharacter
Indicates that one entity affects, shapes, or alters the traits, behavior, or development of another entity’s character.
-
C.
thematicCharacter
Indicates that an entity serves as a central or recurring figure embodying key themes or motifs within a narrative or discourse.
-
D.
mentorCharacter
Indicates that one character serves as a mentor, providing guidance, teaching, or support to another character.
-
E.
storyCharacterizedAs
Indicates that a story is described, portrayed, or defined as having a particular quality, style, or attribute.
- 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_69f348e340d48190b780fae618c51464 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f7764ab1fc81909f9348db87bd7692 |
completed | May 3, 2026, 4:22 p.m. |
| PD | Predicate disambiguation | batch_69f76905d9c88190b1ee810bc9ab644f |
completed | May 3, 2026, 3:25 p.m. |
Created at: April 30, 2026, 11:29 p.m.