Triple
T28900189
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DIN 41612 |
E732931
|
entity |
| Predicate | hasTypicalApplication |
P68291
|
FINISHED |
| Object | rack-based electronic systems |
—
|
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: rack-based electronic systems | Statement: [DIN 41612, hasTypicalApplication, rack-based electronic systems]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalApplication Context triple: [DIN 41612, hasTypicalApplication, rack-based electronic systems]
-
A.
hasApplicationType
Indicates that an entity is associated with or classified by a specific type or category of application.
-
B.
hasTypicalUsageType
Indicates that something is associated with a standard or commonly expected way in which it is used.
-
C.
hasApp
Indicates that an entity possesses, provides, or is associated with a particular application.
-
D.
hasTypicalUseContext
Indicates that something is commonly or characteristically used within a particular situation, setting, or context.
-
E.
hasCommonApplication
chosen
Indicates that two or more entities share at least one typical or frequent use, purpose, or practical application in common.
- 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_69f05b08c2008190ac426a035a2ed66d |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69fd509e6bc08190b263923c2f40fea3 |
completed | May 8, 2026, 2:55 a.m. |
| PD | Predicate disambiguation | batch_69fd4fd1a58881909d4b84de1b24e380 |
completed | May 8, 2026, 2:52 a.m. |
Created at: April 28, 2026, 8:02 a.m.