Triple
T11572644
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bounty Law |
E274427
|
entity |
| Predicate | metafictionalRole |
P12417
|
FINISHED |
| Object | show-within-a-film |
—
|
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: show-within-a-film | Statement: [Bounty Law, metafictionalRole, show-within-a-film]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: metafictionalRole Context triple: [Bounty Law, metafictionalRole, show-within-a-film]
-
A.
hasMetafictionalRole
chosen
Indicates that an entity plays a role within a story that self-consciously comments on, references, or breaks the conventions of fiction itself.
-
B.
metaNarrativeRole
Indicates the narrative function or role that one element (such as a character, voice, or device) plays in commenting on, framing, or reflecting the story itself at a meta-level.
-
C.
literaryRole
Indicates the specific narrative or functional role an entity holds within a literary work or text.
-
D.
narrativeRoleContext
Indicates the contextual narrative function or role an entity plays within a story or discourse (e.g., protagonist, antagonist, narrator) relative to other elements.
-
E.
fictionalNarrator
Indicates that one entity serves as the narrator or storytelling voice within a fictional work that features the other entity.
- 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_69d6aae5ac3c81908d2b0a3a665665b2 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d88dd6913881908becf188c0a7a275 |
completed | April 10, 2026, 5:42 a.m. |
| PD | Predicate disambiguation | batch_69d85dcbacd0819094d4a1237055affa |
completed | April 10, 2026, 2:17 a.m. |
Created at: April 8, 2026, 9:38 p.m.