Triple
T4441574
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barlow lens |
E95782
|
entity |
| Predicate | hasOpticalDesign |
P7246
|
FINISHED |
| Object | negative (diverging) lens group |
—
|
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: negative (diverging) lens group | Statement: [Barlow lens, hasOpticalDesign, negative (diverging) lens group]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOpticalDesign Context triple: [Barlow lens, hasOpticalDesign, negative (diverging) lens group]
-
A.
opticalDesign
chosen
Indicates a relationship where one entity is responsible for creating, specifying, or defining the optical configuration or characteristics of another entity.
-
B.
usesOpticsType
Indicates that one entity employs or is characterized by a specific type of optical system or technology.
-
C.
hasDesignOption
Indicates that an entity is associated with or offers a particular design alternative or configurable design choice.
-
D.
opticalProperty
Indicates a relationship where an entity has or is characterized by a specific optical property, such as how it interacts with or responds to light.
-
E.
hasFocalPlane
Indicates that an optical system or imaging device possesses a specific focal plane where light is brought into focus.
- 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_69b3453ea2b48190a26f154b3b8fece5 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b355ad71588190b1dcad4250472c29 |
completed | March 13, 2026, 12:09 a.m. |
| PD | Predicate disambiguation | batch_69b34f62c180819097ced38da2052207 |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:32 p.m.