Triple
T31538522
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gabrielle Darley |
E804676
|
entity |
| Predicate | narrativeUsedIn |
P115762
|
FINISHED |
| Object | screen story for The Red Kimona |
—
|
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: screen story for The Red Kimona | Statement: [Gabrielle Darley, narrativeUsedIn, screen story for The Red Kimona]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: narrativeUsedIn Context triple: [Gabrielle Darley, narrativeUsedIn, screen story for The Red Kimona]
-
A.
useInNarrative
chosen
Indicates that something is employed as an element or device within a narrative or story.
-
B.
narrative
Indicates that one entity tells, presents, or conveys a story or sequence of events about another entity or situation.
-
C.
containsNarrativeOf
Indicates that one entity includes or presents the story, account, or narrative content of another entity.
-
D.
narratesWith
Indicates that one entity tells, recounts, or presents a story, event, or information in conjunction with or alongside another entity.
-
E.
narrativeType
Indicates the specific kind or category of narrative (e.g., genre, structural form, or storytelling mode) associated with an 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_69f348d03ef88190a2b73d7b94b9e02d |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f79f48acec8190a9d5964581a94f6c |
completed | May 3, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_69f79e4888248190be2f63cdfb5cd7b7 |
completed | May 3, 2026, 7:13 p.m. |
Created at: April 30, 2026, 10:05 p.m.