Triple
T23101787
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carborundum |
E576048
|
entity |
| Predicate | hasGenericUseAsTerm |
P137294
|
FINISHED |
| Object | silicon carbide abrasive |
—
|
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: silicon carbide abrasive | Statement: [Carborundum, hasGenericUseAsTerm, silicon carbide abrasive]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGenericUseAsTerm Context triple: [Carborundum, hasGenericUseAsTerm, silicon carbide abrasive]
-
A.
useOfTerm
chosen
Indicates that one entity employs or applies a specific term or expression in reference to another entity or context.
-
B.
hasGenericName
Indicates that an entity is associated with a non-brand, generic name that designates its general type or class.
-
C.
hasConceptualUse
Indicates that one entity is used or applied in a conceptual, abstract, or theoretical way by another entity.
-
D.
hasCustomTerm
Indicates that an entity is associated with a user-defined or non-standard term specific to a particular context or configuration.
-
E.
hasTerm
Indicates that an entity includes, is associated with, or is defined by a specific term or condition.
- 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_69e245c060b48190a9bd61a47a16db17 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f18de9fa8c81909fd26ff37173b85b |
completed | April 29, 2026, 4:49 a.m. |
| PD | Predicate disambiguation | batch_69ef89e5ce748190b2c3ac3843484127 |
completed | April 27, 2026, 4:08 p.m. |
Created at: April 17, 2026, 3:58 p.m.