Triple
T3358254
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kiss Kiss Bang Bang |
E70655
|
entity |
| Predicate | hasMetafictionalElements |
P23847
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Kiss Kiss Bang Bang, hasMetafictionalElements, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMetafictionalElements Context triple: [Kiss Kiss Bang Bang, hasMetafictionalElements, true]
-
A.
hasMetafictionalRole
Indicates that an entity plays a role within a story that self-consciously comments on, references, or breaks the conventions of fiction itself.
-
B.
hasFictionComponent
Indicates that something includes, contains, or is composed in part of a fictional element or work.
-
C.
hasFictionalForm
Indicates that an entity has a counterpart or representation that exists within a fictional or imaginary context.
-
D.
hasAutobiographicalElements
Indicates that something, such as a work or narrative, contains elements drawn from the creator’s own life or personal experiences.
-
E.
hasNarrativeDevice
chosen
Indicates that one entity employs, contains, or is characterized by a particular narrative device used in storytelling or discourse.
- 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_69ad85a660c48190998489309a3b4869 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb26523cc819091006fde7beb32e4 |
completed | March 8, 2026, 5:31 p.m. |
| PD | Predicate disambiguation | batch_69ada42fbe7c8190b9f185b5ab985f17 |
completed | March 8, 2026, 4:30 p.m. |
Created at: March 8, 2026, 3:13 p.m.