Triple
T1249079
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Snell’s law of refraction |
E26832
|
entity |
| Predicate | symbolDefinition |
P15163
|
FINISHED |
| Object | n1 is refractive index of first medium |
—
|
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: n1 is refractive index of first medium | Statement: [Snell’s law of refraction, symbolDefinition, n1 is refractive index of first medium]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: symbolDefinition Context triple: [Snell’s law of refraction, symbolDefinition, n1 is refractive index of first medium]
-
A.
symbolDescription
chosen
Indicates that a symbol is associated with or defined by a particular descriptive explanation or meaning.
-
B.
symbolType
Indicates the classification or category of a symbol based on its role, form, or function within a given system.
-
C.
scopeDefinedBy
Indicates that the extent or boundaries of one entity’s applicability, influence, or validity are determined or constrained by another entity.
-
D.
symbolInBook
Indicates a relationship where a particular symbol appears or is used within a specific book.
-
E.
pointDefinition
Indicates that one entity serves as the defining description or specification of a particular point in 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_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.