Triple
T9996907
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jenny Slate as Dawn Bellwether |
E197223
|
entity |
| Predicate | characterMotivation |
P91485
|
FINISHED |
| Object | resentmentAgainstPredators |
—
|
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: resentmentAgainstPredators | Statement: [Jenny Slate as Dawn Bellwether, characterMotivation, resentmentAgainstPredators]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterMotivation Context triple: [Jenny Slate as Dawn Bellwether, characterMotivation, resentmentAgainstPredators]
-
A.
characterInspiration
Indicates that one entity serves as the creative or conceptual inspiration for the development or portrayal of another character.
-
B.
characterSetting
Indicates that a character is associated with, appears in, or is situated within a particular setting or environment.
-
C.
character1
Indicates that the subject is identified as the first or primary character in a narrative or context.
-
D.
protagonistCharacteristic
Indicates that a characteristic, trait, or defining quality is attributed to the protagonist in a narrative or scenario.
-
E.
characterTheme
Indicates that a particular theme, motif, or conceptual focus is associated with a given character.
- F. None of above. chosen
Provenance (4 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_69cdcc8aa1a881909879a694496f11a5 |
completed | April 2, 2026, 1:55 a.m. |
| PD | Predicate disambiguation | batch_69cd1da07db88190945bcdab3ca82e71 |
completed | April 1, 2026, 1:29 p.m. |
| PDg | Predicate description generation | batch_69cd358386f48190833c862b5b8c04b2 |
completed | April 1, 2026, 3:10 p.m. |
Created at: March 30, 2026, 8:51 p.m.