Triple
T1462828
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wien displacement law |
E31550
|
entity |
| Predicate | constantApproximateValue |
P9773
|
FINISHED |
| Object | 2.897771955×10^-3 m·K |
—
|
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: 2.897771955×10^-3 m·K | Statement: [Wien displacement law, constantApproximateValue, 2.897771955×10^-3 m·K]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: constantApproximateValue Context triple: [Wien displacement law, constantApproximateValue, 2.897771955×10^-3 m·K]
-
A.
hasApproximateValue
chosen
Indicates that one entity’s value is close to, but not exactly equal to, the value of another entity within an acceptable margin of error.
-
B.
approximates
Indicates that one entity is close to, but not exactly equal to, the value, form, or behavior of another entity.
-
C.
approximationType
Indicates the specific method or scheme used to approximate a value, function, or relationship in a given context.
-
D.
constant
Indicates that the relationship or value does not change across different instances, contexts, or over time.
-
E.
approximateMass
Indicates that one entity has a mass value that is an estimate or close approximation of the mass of another 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_69a49917dfc081909acdbdf5d684f1ef |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c5b6e36c81909c47b2f7e66f17d7 |
completed | March 1, 2026, 11:03 p.m. |
| PD | Predicate disambiguation | batch_69a4c48121e48190946c23c583e5fb64 |
completed | March 1, 2026, 10:58 p.m. |
Created at: March 1, 2026, 8 p.m.