Triple
T1677073
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SUSAT sight |
E36254
|
entity |
| Predicate | magnification |
P20532
|
FINISHED |
| Object | 4× |
—
|
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× | Statement: [SUSAT sight, magnification, 4×]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: magnification Context triple: [SUSAT sight, magnification, 4×]
-
A.
magnitude
Indicates a relationship where a quantitative size, extent, or intensity is assigned to or compared between entities or values.
-
B.
magnitudeScale
Indicates the scale or measurement system used to quantify the magnitude or intensity of something.
-
C.
telephotoOpticalZoom
chosen
Indicates that the relationship involves zooming in optically with a telephoto lens to magnify a subject without digital enlargement.
-
D.
apparentMagnitude
Indicates the observed brightness of an astronomical object as seen from Earth, on a logarithmic scale where lower values correspond to brighter appearances.
-
E.
mirrorCount
Indicates the number of mirrors associated with or present in relation to a given entity or context.
- 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_69a886139ed081909af0940aa9313512 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69ab272a653481908f48aa1eed5de8a4 |
completed | March 6, 2026, 7:12 p.m. |
| PD | Predicate disambiguation | batch_69aa61b2f6288190b2348ef7d7e4672d |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:29 p.m.