Triple
T10737581
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chalet Girl |
E253231
|
entity |
| Predicate | protagonistFormerOccupation |
P21567
|
FINISHED |
| Object | skateboard champion |
—
|
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: skateboard champion | Statement: [Chalet Girl, protagonistFormerOccupation, skateboard champion]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: protagonistFormerOccupation Context triple: [Chalet Girl, protagonistFormerOccupation, skateboard champion]
-
A.
characterFormerOccupation
Indicates that a character previously held a specific occupation but no longer does.
-
B.
featuresProtagonistOccupation
chosen
Indicates that the work’s main character has a specified occupation or job role.
-
C.
protagonistSocialStatus
Indicates the social standing or class position held by the story’s main character in relation to others in their society.
-
D.
protagonistBackground
Indicates that one entity serves as the background, history, or prior circumstances of the protagonist entity in a narrative or story.
-
E.
protagonistDescription
Indicates that a text provides a descriptive summary or characterization of the story’s main protagonist.
- 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_69d6aa5e51e8819095f06881cecf152e |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d710410a04819090036597ac0d271c |
completed | April 9, 2026, 2:34 a.m. |
| PD | Predicate disambiguation | batch_69d6f30df9948190ab3cdc33977fac14 |
completed | April 9, 2026, 12:30 a.m. |
Created at: April 8, 2026, 9:14 p.m.