Triple
T28196622
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Red Special |
E716465
|
entity |
| Predicate | nutMaterial |
P1272
|
FINISHED |
| Object | bakelite |
—
|
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: bakelite | Statement: [Red Special, nutMaterial, bakelite]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nutMaterial Context triple: [Red Special, nutMaterial, bakelite]
-
A.
material
Indicates that one entity is physically composed of, made from, or constructed using the substance or material represented by the other entity.
-
B.
materialUsed
chosen
Indicates that one entity is made from, incorporates, or utilizes the other entity as its material or substance.
-
C.
materialOptions
Indicates that there are one or more possible materials that can be chosen or applied in relation to a given entity or context.
-
D.
crestMaterial
Indicates that one entity is the material from which another entity’s crest is made.
-
E.
materialDepicted
Indicates that a work or representation visually portrays or includes a particular material as part of its subject.
- 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_69efd6b612f48190a72012b520afbd10 |
completed | April 27, 2026, 9:35 p.m. |
| NER | Named-entity recognition | batch_69f642d23ea481908f010394a925b83f |
completed | May 2, 2026, 6:30 p.m. |
| PD | Predicate disambiguation | batch_69f63c6c1a948190b68c0f92c264cc0c |
completed | May 2, 2026, 6:03 p.m. |
Created at: April 27, 2026, 10:28 p.m.