Triple
T15821197
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Dressmaker (film score) |
E383611
|
entity |
| Predicate | narrativeToneSupported |
P5869
|
FINISHED |
| Object | dark comedy |
—
|
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: dark comedy | Statement: [The Dressmaker (film score), narrativeToneSupported, dark comedy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: narrativeToneSupported Context triple: [The Dressmaker (film score), narrativeToneSupported, dark comedy]
-
A.
narrativeStyle
chosen
Indicates how a narrative is told, such as the point of view, tone, and structural approach used to present a story or account.
-
B.
narrativeType
Indicates the specific kind or category of narrative (e.g., genre, structural form, or storytelling mode) associated with an entity.
-
C.
narrativeFormat
Indicates the specific structural or stylistic form in which a narrative is presented or expressed.
-
D.
narratorType
Indicates the narrative perspective or role from which a story or account is being told.
-
E.
supportsNarrativeText
Indicates that one entity provides justification, evidence, or contextual backing that helps explain or validate the narrative content expressed by another 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_69d86da2858c819090cc8481e7207b6e |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e0c4a7ba4881908a2747bf063d79f1 |
completed | April 16, 2026, 11:14 a.m. |
| PD | Predicate disambiguation | batch_69e005418f588190824d91ff7974dada |
completed | April 15, 2026, 9:38 p.m. |
Created at: April 10, 2026, 4:49 a.m.