Triple
T32689713
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Richardson–Dushman equation |
E835820
|
entity |
| Predicate | hasUnitForJ |
P28578
|
FINISHED |
| Object | ampere per square 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: ampere per square meter | Statement: [Richardson–Dushman equation, hasUnitForJ, ampere per square meter]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUnitForJ Context triple: [Richardson–Dushman equation, hasUnitForJ, ampere per square meter]
-
A.
hasUnitIn
Indicates that one entity is contained or measured within another as a unit, specifying a unit-of-measure or component relationship.
-
B.
hasUnitOf
chosen
Indicates that a quantity, measurement, or value is expressed in terms of a specific unit.
-
C.
hasUnitClass
Indicates that an entity is associated with, or categorized under, a particular unit classification or type.
-
D.
hasUnitForForce
Indicates a relationship where a specified unit is used to measure or express a quantity of force.
-
E.
hasUnitsFrom
Indicates that one entity derives, adopts, or uses its measurement units from another specified source entity.
- 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_69f3493211388190993801216afbc2a7 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fba2877b248190a974eb092243c0c4 |
completed | May 6, 2026, 8:20 p.m. |
| PD | Predicate disambiguation | batch_69fb8d06a1b48190a937aa410d159dfa |
completed | May 6, 2026, 6:48 p.m. |
Created at: May 1, 2026, 1:09 a.m.