Triple
T30569078
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sky Masterson |
E778071
|
entity |
| Predicate | primaryMotivationInPlot |
P91485
|
FINISHED |
| Object | winning a bet involving Sarah Brown |
—
|
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: winning a bet involving Sarah Brown | Statement: [Sky Masterson, primaryMotivationInPlot, winning a bet involving Sarah Brown]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryMotivationInPlot Context triple: [Sky Masterson, primaryMotivationInPlot, winning a bet involving Sarah Brown]
-
A.
characterMotivation
chosen
Indicates the underlying reasons, desires, or goals that drive a character’s actions and decisions within a narrative.
-
B.
primaryMotif
Indicates that one entity serves as the main recurring theme or dominant motif associated with another entity.
-
C.
initialMotivation
Indicates the original reason, drive, or purpose that prompts an entity to begin an action, behavior, or process.
-
D.
mainSettingOfStory
Indicates that a location or environment serves as the primary setting in which the events of a story take place.
-
E.
storylineReason
Indicates that one event, action, or situation occurs as a narrative cause or justification for another within a storyline.
- 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_69f2249f8c148190ae7eb3912cde112a |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_6a02fc3890a881908b69b0f2d7cc1ce1 |
completed | May 12, 2026, 10:08 a.m. |
| PD | Predicate disambiguation | batch_6a02fb98438c8190938896c00216b9ec |
completed | May 12, 2026, 10:06 a.m. |
Created at: April 29, 2026, 8:21 p.m.