Triple
T32443876
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Langevin function |
E829089
|
entity |
| Predicate | argumentRepresents |
P54139
|
FINISHED |
| Object | ratio of magnetic energy to thermal energy |
—
|
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: ratio of magnetic energy to thermal energy | Statement: [Langevin function, argumentRepresents, ratio of magnetic energy to thermal energy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: argumentRepresents Context triple: [Langevin function, argumentRepresents, ratio of magnetic energy to thermal energy]
-
A.
argumentOf
Indicates that one entity functions as an argument (participant or operand) in relation to another entity, such as a predicate, event, or expression.
-
B.
areRepresentedBy
chosen
Indicates that one entity serves as a representation, proxy, or stand-in for another entity.
-
C.
fieldRepresents
Indicates that one field or attribute stands for, encodes, or symbolizes another concept, value, or entity.
-
D.
argumentType
Indicates that one entity serves as a specific semantic or syntactic argument role (such as subject, object, or complement) in relation to another entity or event.
-
E.
representsAs
Indicates that one entity serves as a depiction, symbol, or stand-in for another entity in some representational context.
- 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_69f3491d2e5c819092b1c9535beff8ec |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6c2e47f48819080d82e789fa9e3e7 |
completed | May 3, 2026, 3:37 a.m. |
| PD | Predicate disambiguation | batch_69f6ba6eb32c8190bf405b2011fa48f7 |
completed | May 3, 2026, 3:01 a.m. |
Created at: May 1, 2026, 12:55 a.m.