Triple
T31372887
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A Christmas Story: The Musical |
E800212
|
entity |
| Predicate | includesMotive |
P15083
|
FINISHED |
| Object | nostalgia |
—
|
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: nostalgia | Statement: [A Christmas Story: The Musical, includesMotive, nostalgia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includesMotive Context triple: [A Christmas Story: The Musical, includesMotive, nostalgia]
-
A.
hasMotiveOfCriminals
Indicates that the specified motive is attributed to or associated with the criminals in question.
-
B.
depictsMotive
Indicates that one entity visually represents or illustrates the motive, intention, or underlying reason associated with another entity or action.
-
C.
motive
Indicates the underlying reason, intention, or driving force that explains why an entity performs or is associated with a particular action or event.
-
D.
hasMotiveElement
chosen
Indicates that one entity includes, specifies, or is characterized by a particular motive-related component or factor in a broader relationship or action.
-
E.
hasMotiveContext
Indicates that there is contextual information explaining the reasons or motivations behind an action, event, or relationship.
- 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_69f224e84da08190abfc2f17494a33c8 |
completed | April 29, 2026, 3:34 p.m. |
| NER | Named-entity recognition | batch_6a0123d1162c81908182d01ba3ddd236 |
completed | May 11, 2026, 12:33 a.m. |
| PD | Predicate disambiguation | batch_6a01236713d88190b12a567c0dfb2d49 |
completed | May 11, 2026, 12:31 a.m. |
Created at: April 29, 2026, 9:18 p.m.