Triple
T32954507
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Winona Hawkins |
E843058
|
entity |
| Predicate | storyOrigin |
P44758
|
FINISHED |
| Object | adaptation of Elmore Leonard’s Raylan Givens universe |
—
|
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: adaptation of Elmore Leonard’s Raylan Givens universe | Statement: [Winona Hawkins, storyOrigin, adaptation of Elmore Leonard’s Raylan Givens universe]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: storyOrigin Context triple: [Winona Hawkins, storyOrigin, adaptation of Elmore Leonard’s Raylan Givens universe]
-
A.
originStoryIncludes
Indicates that an entity’s origin story contains, involves, or features the referenced element as a component or part of that backstory.
-
B.
historicalOrigin
Indicates the relationship by which one entity serves as the source, origin, or starting point in history for another entity.
-
C.
sourceOfStories
chosen
Indicates that one entity serves as the origin or provider of stories for another entity.
-
D.
hasOriginStoryLocation
Indicates that an entity’s origin story takes place at or is associated with a specific location.
-
E.
originStorySummary
Indicates a brief narrative explaining how something began, was created, or came into existence.
- 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_69f3494a31f481909057136e49b4fe60 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f7221dc9a88190bb8194fcc29c42bc |
completed | May 3, 2026, 10:23 a.m. |
| PD | Predicate disambiguation | batch_69f72153a9188190b02adc84e1be4af8 |
completed | May 3, 2026, 10:20 a.m. |
Created at: May 1, 2026, 1:21 a.m.