Triple
T38560300
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ZN stain |
E928060
|
entity |
| Predicate | microscopyType |
P99734
|
FINISHED |
| Object | light microscopy |
—
|
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: light microscopy | Statement: [ZN stain, microscopyType, light microscopy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: microscopyType Context triple: [ZN stain, microscopyType, light microscopy]
-
A.
microscopeType
chosen
Indicates the specific kind or category of microscope associated with an entity.
-
B.
microscopicStructure
Indicates the detailed arrangement and organization of components at a microscopic scale within an entity.
-
C.
typicalMagnification
Indicates the usual or characteristic degree to which something is enlarged or magnified under normal or standard conditions.
-
D.
laboratoryType
Indicates the specific category or kind of laboratory associated with an entity (e.g., clinical, research, diagnostic).
-
E.
imagingInstrument
Indicates that a particular instrument or device is used to capture or produce an image of a target or subject.
- 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_69f76eb8d1808190a588af29d8b266d6 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fcdaa36f90819093f8661969990c7d |
completed | May 7, 2026, 6:32 p.m. |
| PD | Predicate disambiguation | batch_69fcd8fefc588190b063d7ea1ec87b07 |
completed | May 7, 2026, 6:25 p.m. |
Created at: May 3, 2026, 4:32 p.m.