Triple
T28638532
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Exposed (short film) |
E724856
|
entity |
| Predicate | hasGrittyStorytellingStyle |
P142232
|
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: [Exposed (short film), hasGrittyStorytellingStyle, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGrittyStorytellingStyle Context triple: [Exposed (short film), hasGrittyStorytellingStyle, true]
-
A.
hasDramaticStyle
Indicates that an entity employs or is characterized by a theatrical, emotionally intense, or striking manner of expression or presentation.
-
B.
usesNarrativeStyle
Indicates that one entity employs or adopts a particular narrative style in presenting or structuring content or information.
-
C.
narrativeStyle
Indicates how a narrative is told, such as the point of view, tone, and structural approach used to present a story or account.
-
D.
hasGrittiness
chosen
Indicates that an entity possesses or exhibits a quality of toughness, resilience, or coarse texture/character.
-
E.
hasScreenplayStyle
Indicates that an entity is associated with or characterized by a particular style or manner of screenplay writing.
- 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_69f01d8328c48190bc0e5f9b9b848582 |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_69f67c9fe7b48190b79b4041357edb49 |
completed | May 2, 2026, 10:37 p.m. |
| PD | Predicate disambiguation | batch_69f678cc272081909e5c70f1bc7407f0 |
completed | May 2, 2026, 10:21 p.m. |
Created at: April 28, 2026, 4:42 a.m.