Triple
T15669872
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Japanese prints (Japonisme) |
E377278
|
entity |
| Predicate | keyFormalFeature |
P7153
|
FINISHED |
| Object | flattened pictorial space |
—
|
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: flattened pictorial space | Statement: [Japanese prints (Japonisme), keyFormalFeature, flattened pictorial space]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: keyFormalFeature Context triple: [Japanese prints (Japonisme), keyFormalFeature, flattened pictorial space]
-
A.
keyFeature
chosen
Indicates that something is a primary, distinguishing, or most important feature of an entity.
-
B.
formalCharacteristics
Indicates that one entity specifies or describes the official, structured, or formally defined attributes or properties of another entity.
-
C.
keyFormula
Indicates that a formula serves as the primary or defining expression associated with an entity or relationship.
-
D.
formalismType
Indicates the specific formal system or representational framework in which something (such as a theory, model, or specification) is expressed.
-
E.
logicalForm
Indicates a relationship where an expression is associated with its structured, formal logical representation.
- 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_69d85cd2e28481909d4e975bee20872f |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04f1254508190a77a16b7bfd299ad |
completed | April 16, 2026, 2:53 a.m. |
| PD | Predicate disambiguation | batch_69deda8b36a4819081cb5708fe77ef51 |
completed | April 15, 2026, 12:23 a.m. |
Created at: April 10, 2026, 4:16 a.m.