Triple
T31301685
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | I Did Something Bad |
E798228
|
entity |
| Predicate | hasCinematicFeel |
P145815
|
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: [I Did Something Bad, hasCinematicFeel, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCinematicFeel Context triple: [I Did Something Bad, hasCinematicFeel, true]
-
A.
hasCinematicFeature
chosen
Indicates that something possesses a specific cinematic characteristic, quality, or element related to film or visual storytelling.
-
B.
hasCinematicThemes
Indicates that something incorporates or is characterized by themes, motifs, or stylistic elements commonly associated with cinema or film.
-
C.
hasCinematicShort
Indicates that an entity is associated with or includes a cinematic short film or short-form cinematic content.
-
D.
cinematicForm
Indicates that something is expressed, structured, or realized through the techniques, conventions, or medium of cinema or film.
-
E.
cinematicContext
Indicates the relationship in which something is situated within, shaped by, or relevant to the circumstances, style, or conventions of cinema or film.
- 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_69f224e0bd4c8190aab9b29a73f7aa3c |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f7431c0eec81909ead443e07d75e18 |
completed | May 3, 2026, 12:44 p.m. |
| PD | Predicate disambiguation | batch_69f74143cf708190a12d487884298437 |
completed | May 3, 2026, 12:36 p.m. |
Created at: April 29, 2026, 9:14 p.m.