Triple
T2318908
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tonio Kröger |
E51130
|
entity |
| Predicate | protagonistBackground |
P38047
|
FINISHED |
| Object | bourgeois family |
—
|
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: bourgeois family | Statement: [Tonio Kröger, protagonistBackground, bourgeois family]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: protagonistBackground Context triple: [Tonio Kröger, protagonistBackground, bourgeois family]
-
A.
protagonistDescription
Indicates that a text provides a descriptive summary or characterization of the story’s main protagonist.
-
B.
protagonistOrigin
Indicates that one entity is the origin, source, or starting point of the protagonist in a narrative or story.
-
C.
protagonistBasedOn
Indicates that a fictional work’s main character is modeled on, inspired by, or derived from a particular real or fictional person or entity.
-
D.
protagonistIs
Indicates that one entity serves as the main character or central figure in relation to another entity or narrative context.
-
E.
featuresProtagonistOccupation
Indicates that the work’s main character has a specified occupation or job role.
- F. None of above. chosen
Provenance (4 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_69a88b074b908190ae983dbca7757d88 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abc685f05481909c863b29d1f6bacd |
completed | March 7, 2026, 6:32 a.m. |
| PD | Predicate disambiguation | batch_69abc5909cc48190aab257313542dc49 |
completed | March 7, 2026, 6:28 a.m. |
| PDg | Predicate description generation | batch_69abc682d094819081a96ffb77c4c42a |
completed | March 7, 2026, 6:32 a.m. |
Created at: March 4, 2026, 7:49 p.m.