Triple
T32060410
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jerrys |
E818731
|
entity |
| Predicate | belongsToGenreElement |
P114508
|
FINISHED |
| Object | afterlife mythology in animation |
—
|
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: afterlife mythology in animation | Statement: [Jerrys, belongsToGenreElement, afterlife mythology in animation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: belongsToGenreElement Context triple: [Jerrys, belongsToGenreElement, afterlife mythology in animation]
-
A.
associatedWithGenreElement
chosen
Indicates that something has a connection or linkage to a specific genre-related element (such as a motif, convention, or stylistic feature).
-
B.
containsGenreElement
Indicates that something includes or incorporates an element characteristic of a particular genre.
-
C.
hasGenreRelation
Indicates that there is an association between an entity and a specific genre, specifying the type or category it belongs to.
-
D.
belongsToWorkGenre
Indicates that a creative work is classified under or associated with a particular genre.
-
E.
hasGenreInRoles
Indicates that an entity participates in roles associated with a particular genre or set of genres.
- 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_69f348fdacec8190b9f74375ca3b2094 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69feb5e66224819083b87c3707a5a5e0 |
completed | May 9, 2026, 4:19 a.m. |
| PD | Predicate disambiguation | batch_69feb3bd700c8190991ed200cd3c04db |
completed | May 9, 2026, 4:10 a.m. |
Created at: May 1, 2026, 12:21 a.m.