Triple
T21793015
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | German Impressionism |
E538022
|
entity |
| Predicate | differenceCharacteristic |
P128575
|
FINISHED |
| Object | stronger attachment to local motifs |
—
|
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: stronger attachment to local motifs | Statement: [German Impressionism, differenceCharacteristic, stronger attachment to local motifs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: differenceCharacteristic Context triple: [German Impressionism, differenceCharacteristic, stronger attachment to local motifs]
-
A.
differenceDescription
Indicates a textual explanation that characterizes how two entities differ from each other.
-
B.
contrastCharacteristic
Indicates that two entities are being compared by highlighting opposing or significantly different characteristics between them.
-
C.
distinguishingTrait
chosen
Indicates that a particular characteristic or feature uniquely differentiates one entity from another.
-
D.
valueCharacteristic
Indicates that one entity serves as a value or specific quantitative/qualitative measure that characterizes or describes another entity.
-
E.
distinction
Indicates that one entity is recognized, treated, or classified as different or separate from another.
- 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_69e0c4733f4081909a86622e7e6d15d2 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f06221d1f4819089bb113d808d79c2 |
completed | April 28, 2026, 7:30 a.m. |
| PD | Predicate disambiguation | batch_69e6be751ce881909badced245ef76c7 |
completed | April 21, 2026, 12:01 a.m. |
Created at: April 16, 2026, 6:52 p.m.