Triple
T18215054
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Compton wavelength |
E436130
|
entity |
| Predicate | inverseProportionalTo |
P9781
|
FINISHED |
| Object | particle mass |
—
|
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: particle mass | Statement: [Compton wavelength, inverseProportionalTo, particle mass]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: inverseProportionalTo Context triple: [Compton wavelength, inverseProportionalTo, particle mass]
-
A.
inverselyProportionalTo
chosen
Indicates that as the value of one quantity increases, the value of the other quantity decreases in such a way that their product remains constant.
-
B.
isProportionalityFactorIn
Indicates that one quantity serves as the proportionality factor (constant of proportionality) in a specified proportional relationship or equation.
-
C.
isInverseOf
Indicates that one relation reverses the direction of another, so that if the original relates A to B, its inverse relates B to A.
-
D.
inverseConvolution
Indicates the operation that reverses or undoes a prior convolution, recovering an original signal or function from its convolved form.
-
E.
proportionalTo
Indicates that one quantity varies in constant ratio to another, so changes in one are directly reflected by proportional changes in the other.
- 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_69d8b90dba6481908e119eb9aa4ca0cb |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4e476a6548190bda03190c5f531ad |
completed | April 19, 2026, 2:19 p.m. |
| PD | Predicate disambiguation | batch_69e4332155d88190b106d0dceb4554af |
completed | April 19, 2026, 1:42 a.m. |
Created at: April 10, 2026, 10:32 a.m.