Triple
T26430413
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Emission Impossible |
E664489
|
entity |
| Predicate | mainFocusCharacter |
P77485
|
FINISHED |
| Object | Stewie Griffin |
—
|
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: Stewie Griffin | Statement: [Emission Impossible, mainFocusCharacter, Stewie Griffin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainFocusCharacter Context triple: [Emission Impossible, mainFocusCharacter, Stewie Griffin]
-
A.
characterInFocus
chosen
Indicates that a particular character is the primary subject or focal point within a given context, scene, or narrative segment.
-
B.
currentCharacter
Indicates that an entity is the character presently in focus or being actively considered in a given context or sequence.
-
C.
importFocus
Indicates that attention, priority, or emphasis is being brought into or concentrated on a particular entity or aspect.
-
D.
canonicalFocus
Indicates that one entity is the primary or most representative focus or point of attention in relation to another entity.
-
E.
hasCharacterFocus
Indicates that a work, scene, or segment centers primarily on a particular character’s experiences, perspective, or development.
- 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_69ee883ad6a4819088f918e76122d690 |
completed | April 26, 2026, 9:48 p.m. |
| NER | Named-entity recognition | batch_69f611bd3ec0819080f559e2cb3889a0 |
completed | May 2, 2026, 3:01 p.m. |
| PD | Predicate disambiguation | batch_69f60b89cc048190a9feb24466006be0 |
completed | May 2, 2026, 2:34 p.m. |
Created at: April 26, 2026, 11:48 p.m.