Triple
T2863813
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miho Museum |
E63387
|
entity |
| Predicate | buildingMaterials |
P1272
|
FINISHED |
| Object | French limestone |
—
|
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: French limestone | Statement: [Miho Museum, buildingMaterials, French limestone]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: buildingMaterials Context triple: [Miho Museum, buildingMaterials, French limestone]
-
A.
wallMaterial
Indicates that one entity is the material from which a wall or walls of another entity are constructed.
-
B.
buildingMaterialTradition
Indicates the customary or historically established use of particular materials in the construction of a building or structure.
-
C.
materialUsed
chosen
Indicates that one entity is made from, incorporates, or utilizes the other entity as its material or substance.
-
D.
ceilingMaterial
Indicates the material from which a ceiling is constructed or finished.
-
E.
constructionType
Indicates the specific method or style by which something is built or constructed.
- 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_69ab4c41e8c08190a9e8f5249cc12610 |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abdfb853908190aa2fd492e9fa5e87 |
completed | March 7, 2026, 8:20 a.m. |
| PD | Predicate disambiguation | batch_69abdd123ec48190af50a1859aea50b7 |
completed | March 7, 2026, 8:08 a.m. |
Created at: March 6, 2026, 10:02 p.m.