Triple
T12514465
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | uniq |
E299160
|
entity |
| Predicate | examplePipeline |
P28421
|
FINISHED |
| Object | sort file | uniq |
—
|
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: sort file | uniq | Statement: [uniq, examplePipeline, sort file | uniq]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: examplePipeline Context triple: [uniq, examplePipeline, sort file | uniq]
-
A.
pipeline
chosen
Indicates a sequential process or workflow where the output of one stage is passed as input to the next to achieve a final result.
-
B.
exampleType
Indicates that one entity serves as a representative or illustrative instance of the type or category defined by another entity.
-
C.
exampleTopic
Indicates that something serves as an illustrative or representative instance of a broader topic or concept.
-
D.
exampleImplementation
Indicates that one entity serves as a concrete, illustrative implementation or instance of another, more general concept, design, or specification.
-
E.
exampleApplication
Indicates that something serves as a representative or illustrative instance of how an application is used or functions.
- 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_69d6ada4cd388190ae3bbf83ff87057a |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d954b867dc8190af8a70f797e4d133 |
completed | April 10, 2026, 7:51 p.m. |
| PD | Predicate disambiguation | batch_69d954096af88190b6be81b008c82139 |
completed | April 10, 2026, 7:48 p.m. |
Created at: April 8, 2026, 9:57 p.m.