Triple
T3633049
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wood–Anderson torsion seismometer |
E77001
|
entity |
| Predicate | typicalMagnification |
P49706
|
FINISHED |
| Object | about 2800 at 0.8 seconds |
—
|
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: about 2800 at 0.8 seconds | Statement: [Wood–Anderson torsion seismometer, typicalMagnification, about 2800 at 0.8 seconds]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalMagnification Context triple: [Wood–Anderson torsion seismometer, typicalMagnification, about 2800 at 0.8 seconds]
-
A.
telephotoOpticalZoom
Indicates that the relationship involves zooming in optically with a telephoto lens to magnify a subject without digital enlargement.
-
B.
focalLength
Indicates the distance between a lens or mirror and its focal point, determining how strongly it converges or diverges light.
-
C.
objectiveLensDiameter
Indicates the diameter of the objective lens used in an optical device, such as a camera or telescope.
-
D.
typicalResolution
Indicates the usual or standard level of detail or clarity at which something (such as an image, display, or representation) is normally rendered or presented.
-
E.
typicalWidth
Indicates the usual or characteristic width associated with an entity, as opposed to an exact or measured width in a specific instance.
- 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_69ad85dd0be48190b738990cb20c4731 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc30457608190840fb5b33f9965c4 |
completed | March 8, 2026, 6:42 p.m. |
| PD | Predicate disambiguation | batch_69adb842be7c8190b7dfdb7c906f294c |
completed | March 8, 2026, 5:56 p.m. |
| PDg | Predicate description generation | batch_69adb902e61c81908f10494f828e260f |
completed | March 8, 2026, 5:59 p.m. |
Created at: March 8, 2026, 3:23 p.m.