Triple
T25174707
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Syrie Maugham |
E630414
|
entity |
| Predicate | usedMaterialOrTechnique |
P1272
|
FINISHED |
| Object | white upholstery and fabrics |
—
|
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: white upholstery and fabrics | Statement: [Syrie Maugham, usedMaterialOrTechnique, white upholstery and fabrics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedMaterialOrTechnique Context triple: [Syrie Maugham, usedMaterialOrTechnique, white upholstery and fabrics]
-
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.
usedByTechnique
Indicates that a particular technique makes use of or employs the referenced entity as part of its method or process.
-
D.
artisticTechnique
Indicates the method, style, or process used to create or execute an artistic work.
-
E.
traditionalMaterial
Indicates that something is made from, incorporates, or is characterized by materials associated with long-established or customary practices.
- 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_69e75a87c9b88190ab60731902a99750 |
completed | April 21, 2026, 11:07 a.m. |
| NER | Named-entity recognition | batch_69f6135293908190809e255bf6334760 |
completed | May 2, 2026, 3:08 p.m. |
| PD | Predicate disambiguation | batch_69f611a72780819082f44e66ca2c6ac9 |
completed | May 2, 2026, 3 p.m. |
Created at: April 21, 2026, 12:22 p.m.