Triple
T29986389
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Unix philosophy |
E761745
|
entity |
| Predicate | typicalExampleTool |
P135707
|
FINISHED |
| Object | grep |
—
|
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: grep | Statement: [Unix philosophy, typicalExampleTool, grep]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalExampleTool Context triple: [Unix philosophy, typicalExampleTool, grep]
-
A.
toolUseExamples
Indicates that one entity provides example instances or demonstrations of how a particular tool is or can be used by another entity.
-
B.
notableExampleBy
Indicates that something serves as a prominent or illustrative example provided or created by a particular entity.
-
C.
isCanonicalExampleOf
chosen
Indicates that something serves as a standard or typical instance that exemplifies a concept, category, or pattern.
-
D.
exampleType
Indicates that one entity serves as a representative or illustrative instance of the type or category defined by another entity.
-
E.
usedAsExampleIn
Indicates that one entity is cited or presented as an illustrative example within another entity, such as a text, discussion, or explanation.
- 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_69f2246851148190b8e76206db94b105 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_6a0324c2d618819093f7e6424b0f5baf |
completed | May 12, 2026, 1:01 p.m. |
| PD | Predicate disambiguation | batch_6a0324292e588190b37d0c3016ea2062 |
completed | May 12, 2026, 12:59 p.m. |
Created at: April 29, 2026, 6:36 p.m.