Triple
T15293352
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rippl-Rónai Museum |
E365585
|
entity |
| Predicate | languageOfInformationMaterials |
P32511
|
FINISHED |
| Object | Hungarian |
—
|
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: Hungarian | Statement: [Rippl-Rónai Museum, languageOfInformationMaterials, Hungarian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfInformationMaterials Context triple: [Rippl-Rónai Museum, languageOfInformationMaterials, Hungarian]
-
A.
languageOfMaterial
chosen
Indicates the language in which a given material, resource, or content is expressed or presented.
-
B.
languageOfSources
Indicates that the specified language is the language in which the referenced sources or source materials are expressed.
-
C.
languageOfInformationCenter
Indicates the language in which an information center communicates or provides its information resources.
-
D.
languageOfProduct
Indicates the language in which a product is written, labeled, presented, or otherwise made available.
-
E.
languageOfWritings
Indicates that a specified language is the one in which certain writings or written works are composed.
- 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_69d85a103d9081908c1ea6c4c73ac8e3 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03682ea488190ac82fdbd0e855d34 |
completed | April 16, 2026, 1:08 a.m. |
| PD | Predicate disambiguation | batch_69deca935e2c8190b640987ddfc542b9 |
completed | April 14, 2026, 11:15 p.m. |
Created at: April 10, 2026, 3:15 a.m.