Triple
T3921449
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fermi (unit) |
E88967
|
entity |
| Predicate | typicalScale |
P46165
|
FINISHED |
| Object | proton radius |
—
|
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: proton radius | Statement: [Fermi (unit), typicalScale, proton radius]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalScale Context triple: [Fermi (unit), typicalScale, proton radius]
-
A.
typicalRange
Indicates the usual or expected range of values, conditions, or states within which something normally occurs or applies.
-
B.
typicalLength
Indicates the usual or characteristic length associated with an entity or phenomenon.
-
C.
typicalHeight
Indicates the usual or characteristic height associated with an entity, such as a person, object, or species.
-
D.
associatedScale
chosen
Indicates that one entity is linked or connected to a particular scale used to measure, classify, or evaluate it.
-
E.
areaScale
Indicates a proportional relationship where one area value is a scaled (enlarged or reduced) version of another by a specific factor.
- 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.