Triple
T26408492
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Whirlpool |
E663894
|
entity |
| Predicate | compressionFunctionConstruction |
P130697
|
FINISHED |
| Object | Miyaguchi–Preneel |
—
|
NE NERFINISHED |
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: Miyaguchi–Preneel | Statement: [Whirlpool, compressionFunctionConstruction, Miyaguchi–Preneel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: compressionFunctionConstruction Context triple: [Whirlpool, compressionFunctionConstruction, Miyaguchi–Preneel]
-
A.
compressionFunctionStructure
Indicates the structural or organizational characteristics that define how a compression function is composed or implemented.
-
B.
compressionFunctionType
chosen
Indicates the specific kind or category of compression function applied in a compression process or algorithm.
-
C.
compressionType
Indicates the method or format used to compress data or content in the relationship.
-
D.
compressionMode
Indicates the specific method or setting used to compress data or content in a given context.
-
E.
compressionGoal
Indicates the target level or outcome of data size reduction that a compression process aims to achieve.
- 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_69ee883931888190901be96d75ee23cc |
completed | April 26, 2026, 9:48 p.m. |
| NER | Named-entity recognition | batch_69f612607c388190ab61d1ac7d18e08d |
completed | May 2, 2026, 3:04 p.m. |
| PD | Predicate disambiguation | batch_69f611a9272881909093360472be832c |
completed | May 2, 2026, 3 p.m. |
Created at: April 26, 2026, 11:36 p.m.