Triple
T6364955
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tahkuna Lighthouse |
E143201
|
entity |
| Predicate | originalOpticType |
P7239
|
FINISHED |
| Object | Fresnel lens |
—
|
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: Fresnel lens | Statement: [Tahkuna Lighthouse, originalOpticType, Fresnel lens]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originalOpticType Context triple: [Tahkuna Lighthouse, originalOpticType, Fresnel lens]
-
A.
usesOpticsType
chosen
Indicates that one entity employs or is characterized by a specific type of optical system or technology.
-
B.
originalLens
Indicates that one lens is the initial or source lens from which another lens or lens configuration is derived or referenced.
-
C.
lensType
Indicates the specific kind or category of lens associated with or used by an entity.
-
D.
objectiveLensDiameter
Indicates the diameter of the objective lens used in an optical device, such as a camera or telescope.
-
E.
opticalDesign
Indicates a relationship where one entity is responsible for creating, specifying, or defining the optical configuration or characteristics 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_69c008d8c61081908bcaf61510d881ed |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0680ed0148190b6e310b15b3449ff |
completed | March 22, 2026, 10:07 p.m. |
| PD | Predicate disambiguation | batch_69c060ee055081908c79a1d151bd74cd |
completed | March 22, 2026, 9:36 p.m. |
Created at: March 22, 2026, 4:32 p.m.