Triple
T33210692
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rick Dockery |
E850148
|
entity |
| Predicate | primaryThemeOfStory |
P150352
|
FINISHED |
| Object | second chances |
—
|
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: second chances | Statement: [Rick Dockery, primaryThemeOfStory, second chances]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryThemeOfStory Context triple: [Rick Dockery, primaryThemeOfStory, second chances]
-
A.
primaryStoryThemes
chosen
Indicates the main recurring ideas or motifs that characterize and unify a story’s narrative.
-
B.
mainSettingOfStory
Indicates that a location or environment serves as the primary setting in which the events of a story take place.
-
C.
primaryThemeOrigin
Indicates that the primary thematic content of something (e.g., a work or discourse) originates from or is derived from a particular source or context.
-
D.
primaryMotif
Indicates that one entity serves as the main recurring theme or dominant motif associated with another entity.
-
E.
primaryTone
Indicates the main or dominant emotional or stylistic quality characterizing something, in contrast to any secondary or supporting tones.
- 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_69f3495fb92c819083ce65d0ddee7a76 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a037c894b488190bcbec2eccaff4a01 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379f338b881908e5593e45d764f4d |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:30 a.m.