Triple
T3921456
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fermi (unit) |
E88967
|
entity |
| Predicate | scaleRelativeToMeter |
P51035
|
FINISHED |
| Object | 1 fermi = 0.000000000000001 meter |
—
|
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: 1 fermi = 0.000000000000001 meter | Statement: [Fermi (unit), scaleRelativeToMeter, 1 fermi = 0.000000000000001 meter]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scaleRelativeToMeter Context triple: [Fermi (unit), scaleRelativeToMeter, 1 fermi = 0.000000000000001 meter]
-
A.
magnitudeScale
Indicates the scale or measurement system used to quantify the magnitude or intensity of something.
-
B.
areaScale
Indicates a proportional relationship where one area value is a scaled (enlarged or reduced) version of another by a specific factor.
-
C.
meter
Indicates a measurement relationship where one entity quantifies the length, distance, or extent of another in meters.
-
D.
usesScaleDegrees
Indicates that something is expressed, analyzed, or organized in terms of musical scale degrees rather than absolute pitches.
-
E.
valueRelativeToMainUnit
chosen
Indicates how a value is expressed in relation to a primary or reference unit, such as a main measurement or base quantity.
- 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_69aed955229881909e85e73ffab1d343 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef188b474819087680db42b04ecdd |
completed | March 9, 2026, 4:12 p.m. |
| PD | Predicate disambiguation | batch_69aee75eedcc81908088ff4dbb8be56b |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:22 p.m.