Triple
T1249109
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Snell’s law of refraction |
E26832
|
entity |
| Predicate | mathematicalType |
P12675
|
FINISHED |
| Object | trigonometric relation |
—
|
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: trigonometric relation | Statement: [Snell’s law of refraction, mathematicalType, trigonometric relation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mathematicalType Context triple: [Snell’s law of refraction, mathematicalType, trigonometric relation]
-
A.
mathematicallyUses
Indicates that one entity employs or applies another entity within a mathematical context, such as in a formula, proof, computation, or theoretical framework.
-
B.
mathematicallyExpressedBy
chosen
Indicates that something (such as a concept, quantity, or relationship) is represented or captured using a specific mathematical expression or formulation.
-
C.
mathematicalSubjectClassification
Indicates that one entity classifies the mathematical subject area or field to which another entity (such as a work, concept, or topic) belongs.
-
D.
derivationType
Indicates the specific manner or process by which one entity is derived or obtained from another.
-
E.
mathematicallyFormulatedBy
Indicates that something (such as a concept, model, or theory) is expressed or defined using mathematical formulations created by a particular agent.
- 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_69a49487a9c48190ba9b05348fd1b53f |
completed | March 1, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69a4bf83b32c81908648e5748b897247 |
completed | March 1, 2026, 10:36 p.m. |
| PD | Predicate disambiguation | batch_69a4bb6b075881908e867c25b5080e25 |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:47 p.m.