Triple
T1196320
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Micromegas detectors |
E25675
|
entity |
| Predicate | hasSpatialResolution |
P25684
|
FINISHED |
| Object | of order 50–100 micrometers |
—
|
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: of order 50–100 micrometers | Statement: [Micromegas detectors, hasSpatialResolution, of order 50–100 micrometers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSpatialResolution Context triple: [Micromegas detectors, hasSpatialResolution, of order 50–100 micrometers]
-
A.
spectralResolution
Indicates the fineness with which a system can distinguish or separate different wavelengths or frequencies within a spectrum.
-
B.
hasApproximateDistanceScale
Indicates that one entity is related to another by a distance measure that is approximate or estimated rather than exact.
-
C.
allowsSpatialCurvature
Indicates that one entity permits or enables the presence or variation of spatial curvature in relation to another entity or context.
-
D.
hasDimensionsApprox
Indicates that an entity has physical dimensions that are known only approximately, rather than as exact measurements.
-
E.
displayResolution
Indicates the relationship specifying the width and height dimensions at which visual content is rendered or shown on a display.
- F. None of above. chosen
Provenance (4 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_69a49429f5ec8190a6a205eb0ae81e5e |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bd7a756c819085d695acfffeaceb |
completed | March 1, 2026, 10:28 p.m. |
| PD | Predicate disambiguation | batch_69a4bb5d40a08190b7682d8ef8075421 |
completed | March 1, 2026, 10:19 p.m. |
| PDg | Predicate description generation | batch_69a4bc49693c8190978ec63a5171d342 |
completed | March 1, 2026, 10:23 p.m. |
Created at: March 1, 2026, 7:46 p.m.