Triple
T20746780
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Disney's Winnie the Pooh |
E510605
|
entity |
| Predicate | hasCharacterDesign |
P1529
|
FINISHED |
| Object | rounded, soft character style |
—
|
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: rounded, soft character style | Statement: [Disney's Winnie the Pooh, hasCharacterDesign, rounded, soft character style]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCharacterDesign Context triple: [Disney's Winnie the Pooh, hasCharacterDesign, rounded, soft character style]
-
A.
characterDesigner
Indicates a relationship where an entity is responsible for designing or creating the visual or conceptual characteristics of a character.
-
B.
hasDesign
chosen
Indicates that one entity possesses, embodies, or is characterized by a particular design associated with another entity.
-
C.
hasCharacterAppearance
Indicates that a character appears or is visually represented within a given work, scene, or context.
-
D.
hasIllustratedCharacters
Indicates that something includes or features characters that are depicted through illustrations.
-
E.
hasHumanCharacters
Indicates that the subject includes or features characters that are human beings.
- 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_69e0b4c845e88190b4c5f3ae79291182 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c225c564819088f2461467698095 |
completed | April 21, 2026, 12:17 a.m. |
| PD | Predicate disambiguation | batch_69e5c0509608819080cdbf47fcddfe36 |
completed | April 20, 2026, 5:57 a.m. |
Created at: April 16, 2026, 12:33 p.m.