Triple
T299402
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peter Schlemihls wundersame Geschichte |
E6164
|
entity |
| Predicate | centralMotif |
P6627
|
FINISHED |
| Object | sale of a shadow |
—
|
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: sale of a shadow | Statement: [Peter Schlemihls wundersame Geschichte, centralMotif, sale of a shadow]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: centralMotif Context triple: [Peter Schlemihls wundersame Geschichte, centralMotif, sale of a shadow]
-
A.
primaryMotif
Indicates that one entity serves as the main recurring theme or dominant motif associated with another entity.
-
B.
centralIn
Indicates that one entity occupies a central or most important position within another entity, context, or structure.
-
C.
centralText
Indicates that one text element is positioned or designated as the central or primary text relative to surrounding content or layout.
-
D.
hasCentralTheme
chosen
Indicates that one entity serves as the primary or dominant theme or subject matter of another entity.
-
E.
secondaryHub
Indicates that an entity functions as a secondary or backup hub in relation to a primary hub within a network or system.
- 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_69a2e79114b081909490b3bf5a5dbb51 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2ea0dd1dc8190aecd5afdeb2fd74b |
completed | Feb. 28, 2026, 1:13 p.m. |
| PD | Predicate disambiguation | batch_69a2e9398df08190af40063a2de7a1d0 |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:06 p.m.