Triple
T25049424
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | X-ray microscopy |
E627333
|
entity |
| Predicate | usesOptics |
P134872
|
FINISHED |
| Object | capillary optics |
—
|
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: capillary optics | Statement: [X-ray microscopy, usesOptics, capillary optics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesOptics Context triple: [X-ray microscopy, usesOptics, capillary optics]
-
A.
usesOpticsType
Indicates that one entity employs or is characterized by a specific type of optical system or technology.
-
B.
hasOpticalElement
chosen
Indicates that one entity includes, contains, or is equipped with a specific optical element as a component or part.
-
C.
opticalDesign
Indicates a relationship where one entity is responsible for creating, specifying, or defining the optical configuration or characteristics of another entity.
-
D.
usesAsLens
Indicates that one entity employs another entity as a lens or optical element through which to view, focus, or modify light or images.
-
E.
usesLensMount
Indicates that one device or component is designed to accept, attach to, or operate with a specific type of lens mount.
- 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_69e2ff2b4c80819087c916b2b16241b9 |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f47b865df48190bf4b6d3e9f9305e6 |
completed | May 1, 2026, 10:08 a.m. |
| PD | Predicate disambiguation | batch_69f4682c8a3c8190adbfaac99474eaaf |
completed | May 1, 2026, 8:45 a.m. |
Created at: April 18, 2026, 6:08 a.m.