Triple
T8635429
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fizeau experiment |
E204510
|
entity |
| Predicate | approximateUncertainty |
P52586
|
FINISHED |
| Object | on the order of a few percent |
—
|
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: on the order of a few percent | Statement: [Fizeau experiment, approximateUncertainty, on the order of a few percent]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateUncertainty Context triple: [Fizeau experiment, approximateUncertainty, on the order of a few percent]
-
A.
hasApproximateValueUncertainty
chosen
Indicates that the value of something is known only approximately and carries an associated degree or range of uncertainty.
-
B.
relativeStandardUncertainty
Indicates the ratio of a measurement’s standard uncertainty to the measured value, expressing uncertainty relative to the magnitude of the quantity.
-
C.
hasUncertainty
Indicates that the relationship or value is associated with some level or type of uncertainty rather than being fully definite or precise.
-
D.
approximates
Indicates that one entity is close to, but not exactly equal to, the value, form, or behavior of another entity.
-
E.
valueSIWithUncertainty
Indicates that a numerical value is expressed in SI units along with an associated measure of its uncertainty.
- 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_69ca834b903c8190add96cc651e1a477 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc47944d1c819081f448f14d04bf9d |
completed | March 31, 2026, 10:15 p.m. |
| PD | Predicate disambiguation | batch_69cc455d6d448190a2da2a319ac78c37 |
completed | March 31, 2026, 10:06 p.m. |
Created at: March 30, 2026, 6:27 p.m.