Triple
T29340661
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Domino Hurley |
E744026
|
entity |
| Predicate | narrativeStyleOfWork |
P5869
|
FINISHED |
| Object | film noir-inspired |
—
|
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: film noir-inspired | Statement: [Domino Hurley, narrativeStyleOfWork, film noir-inspired]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: narrativeStyleOfWork Context triple: [Domino Hurley, narrativeStyleOfWork, film noir-inspired]
-
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.
narrativeThemeOfWork
Indicates that one concept or motif functions as a central narrative theme within a particular creative work.
-
C.
narrativeFocusOfWork
Indicates that a particular element (such as a character, event, or theme) is the primary narrative focus or central subject of a given work.
-
D.
narrativeSettingOfWork
Indicates that a particular place, time, or context serves as the narrative setting in which a work’s story or events occur.
-
E.
usesNarrativeStyle
Indicates that one entity employs or adopts a particular narrative style in presenting or structuring content or information.
- 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_69f09126cfcc8190899b16fbf3c2bf7b |
completed | April 28, 2026, 10:51 a.m. |
| NER | Named-entity recognition | batch_69f707f7959881908f037f0d6b1d0c36 |
completed | May 3, 2026, 8:31 a.m. |
| PD | Predicate disambiguation | batch_69f700fc274c8190a128593dc7c7abd0 |
completed | May 3, 2026, 8:02 a.m. |
Created at: April 28, 2026, 1:33 p.m.