Triple
T5775150
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Klaus von Klitzing |
E127420
|
entity |
| Predicate | RKValueApprox |
P9773
|
FINISHED |
| Object | 25812.807 ohms |
—
|
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: 25812.807 ohms | Statement: [Klaus von Klitzing, RKValueApprox, 25812.807 ohms]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: RKValueApprox Context triple: [Klaus von Klitzing, RKValueApprox, 25812.807 ohms]
-
A.
approximationType
Indicates the specific method or scheme used to approximate a value, function, or relationship in a given context.
-
B.
approximates
Indicates that one entity is close to, but not exactly equal to, the value, form, or behavior of another entity.
-
C.
runtimeApprox
Indicates an approximate or estimated duration of time that something (such as a process, program, or event) takes to run or complete.
-
D.
hasApproximateValue
chosen
Indicates that one entity’s value is close to, but not exactly equal to, the value of another entity within an acceptable margin of error.
-
E.
approximationFamily
Indicates a relationship where one entity serves as an approximation or approximate representation of another within a defined family or set of approximations.
- 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_69c008361fa88190aefa4dc41b051e7f |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02acb12c081908e4beee4a957f9f9 |
completed | March 22, 2026, 5:45 p.m. |
| PD | Predicate disambiguation | batch_69c021d0c6088190ba670ddcdbf5ca3e |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:50 p.m.