Triple
T38686546
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pete (Disney character) (voice) |
E949133
|
entity |
| Predicate | portraysAlignment |
P150464
|
FINISHED |
| Object | villain |
—
|
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: villain | Statement: [Pete (Disney character) (voice), portraysAlignment, villain]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portraysAlignment Context triple: [Pete (Disney character) (voice), portraysAlignment, villain]
-
A.
speciesAlignment
Indicates how closely related or compatible two species are in terms of traits, behavior, or evolutionary relationship.
-
B.
revealedAlignment
Indicates that one entity has disclosed or made known the moral, ethical, or factional stance (alignment) of another entity.
-
C.
characterAlignment
Indicates the moral or ethical stance a character holds, typically along axes such as good–evil and lawful–chaotic.
-
D.
portraysRoleTrait
chosen
Indicates that one entity depicts or represents a particular role or character trait of another entity.
-
E.
portraysPositively
Indicates that one entity represents or depicts another entity in a favorable or positive manner.
- 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_69f76efe16148190befd5dd59c3dfeaa |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69ffdf47d9608190830ca23d9cef6409 |
completed | May 10, 2026, 1:28 a.m. |
| PD | Predicate disambiguation | batch_69ffdf00e2b4819082dd5cb78f316baf |
completed | May 10, 2026, 1:27 a.m. |
Created at: May 3, 2026, 4:33 p.m.