Triple
T37897773
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sogetsu school |
E945327
|
entity |
| Predicate | uses material |
P1272
|
FINISHED |
| Object | traditional plant materials |
—
|
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: traditional plant materials | Statement: [Sogetsu school, uses material, traditional plant materials]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: uses material Context triple: [Sogetsu school, uses material, traditional plant materials]
-
A.
materialUsed
chosen
Indicates that one entity is made from, incorporates, or utilizes the other entity as its material or substance.
-
B.
usesMaterialBy
Indicates that one entity makes use of or employs a material that is provided, specified, or created by another entity.
-
C.
usesSupportMaterial
Indicates that an entity relies on or incorporates additional supporting materials or resources to carry out an action or fulfill a function.
-
D.
supportsMaterial
Indicates that one entity provides structural or functional support to a material entity, enabling it to be held, stabilized, or borne.
-
E.
material
Indicates that one entity is physically composed of, made from, or constructed using the substance or material represented by the other entity.
- 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_69f76ef0e8708190987c7254ed8c7abe |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fbc36ce1f88190a7fa1656b714e107 |
completed | May 6, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69fbbd166a488190b1bf9316b0790801 |
completed | May 6, 2026, 10:13 p.m. |
Created at: May 3, 2026, 4:19 p.m.