Triple
T27528721
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Multiple Mirror Telescope |
E694909
|
entity |
| Predicate | originalDesignApertureEquivalent |
P195673
|
FINISHED |
| Object | 4.5-metre effective aperture |
—
|
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: 4.5-metre effective aperture | Statement: [Multiple Mirror Telescope, originalDesignApertureEquivalent, 4.5-metre effective aperture]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originalDesignApertureEquivalent Context triple: [Multiple Mirror Telescope, originalDesignApertureEquivalent, 4.5-metre effective aperture]
-
A.
equivalentFocalLengthOnAPSC
Indicates the focal length on an APS-C sensor that would provide the same field of view as a given focal length on a full-frame (35mm) sensor.
-
B.
minimumAperture
Indicates the smallest opening or aperture size that a system, device, or component can achieve or operate with.
-
C.
maximumAperture
Indicates the widest opening size that an optical system (such as a lens) can achieve to allow light to pass through.
-
D.
hasAperture
Indicates that one entity possesses or is characterized by a specific opening, gap, or aperture.
-
E.
focalLength
Indicates the distance between a lens or mirror and its focal point, determining how strongly it converges or diverges light.
- 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_69ef538550208190aa9de8e2cb260d93 |
completed | April 27, 2026, 12:16 p.m. |
| NER | Named-entity recognition | batch_69fddf721c1481909301a0f379368f10 |
completed | May 8, 2026, 1:04 p.m. |
| PD | Predicate disambiguation | batch_69fddda1ae7c8190b5848ff9a9e39826 |
completed | May 8, 2026, 12:57 p.m. |
| PDg | Predicate description generation | batch_69fddf70ab10819088b76bd98e208354 |
completed | May 8, 2026, 1:04 p.m. |
Created at: April 27, 2026, 1:25 p.m.