Triple
T30358147
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nikon Z-mount lenses |
E772201
|
entity |
| Predicate | opticalDesignGoal |
P33716
|
FINISHED |
| Object | high edge-to-edge sharpness |
—
|
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: high edge-to-edge sharpness | Statement: [Nikon Z-mount lenses, opticalDesignGoal, high edge-to-edge sharpness]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: opticalDesignGoal Context triple: [Nikon Z-mount lenses, opticalDesignGoal, high edge-to-edge sharpness]
-
A.
opticalDesign
Indicates a relationship where one entity is responsible for creating, specifying, or defining the optical configuration or characteristics of another entity.
-
B.
optimizationTarget
chosen
Indicates that one entity is the goal or objective that another entity is trying to improve, optimize, or make more efficient.
-
C.
calibrationGoal
Indicates that an entity serves as a target or reference state used to guide or evaluate the calibration of another entity or system.
-
D.
engineeringGoal
Indicates that an entity has a specific engineering-related objective, target, or desired outcome it is intended to achieve or support.
-
E.
appliesToDesignGoal
Indicates that something (such as a method, rule, or constraint) is relevant or intended to be used for achieving a particular design goal.
- 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_69f2248c6f5c8190a6177842bf791a3c |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f682417ec08190982dd9acf7219742 |
completed | May 2, 2026, 11:01 p.m. |
| PD | Predicate disambiguation | batch_69f67e40af9881908de3a4aa15f70a83 |
completed | May 2, 2026, 10:44 p.m. |
Created at: April 29, 2026, 7:57 p.m.