Triple
T2682838
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MICROSCOPE |
E57413
|
entity |
| Predicate | achievedPrecision |
P1518
|
FINISHED |
| Object | equivalence principle tested to about 10^-15 |
—
|
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: equivalence principle tested to about 10^-15 | Statement: [MICROSCOPE, achievedPrecision, equivalence principle tested to about 10^-15]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: achievedPrecision Context triple: [MICROSCOPE, achievedPrecision, equivalence principle tested to about 10^-15]
-
A.
precision
Indicates the degree to which an action, measurement, or outcome is carried out with exactness, minimal deviation, and fine-grained accuracy.
-
B.
achieved
chosen
Indicates that an entity successfully reached, obtained, or accomplished a specified goal, result, or state.
-
C.
calibratedFor
Indicates that something has been adjusted or tuned to operate accurately or optimally for a specific target, condition, or context.
-
D.
supersededInPrecisionBy
Indicates that one entity’s level of precision has been replaced or overtaken by another entity’s greater precision.
-
E.
completionRate
Indicates the proportion of a task, process, or set of items that has been finished relative to its total intended amount.
- 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_69ab4a5028388190a36f3baf1588309e |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd9d602848190b638e417e710a555 |
completed | March 7, 2026, 7:55 a.m. |
| PD | Predicate disambiguation | batch_69abd81c9b4c81908e5e0da6ac5f828b |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:54 p.m.