Triple
T28533726
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | EPIC |
E722105
|
entity |
| Predicate | imageResolutionAtSubsatellitePoint |
P25684
|
FINISHED |
| Object | approximately 10 km |
—
|
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: approximately 10 km | Statement: [EPIC, imageResolutionAtSubsatellitePoint, approximately 10 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: imageResolutionAtSubsatellitePoint Context triple: [EPIC, imageResolutionAtSubsatellitePoint, approximately 10 km]
-
A.
hasSpatialResolution
chosen
Indicates that something is characterized by a specific level of spatial detail or granularity at which it can represent or distinguish features in space.
-
B.
sensorResolution
Indicates the level of detail or precision with which a sensor can measure or distinguish changes in the observed quantity or environment.
-
C.
imageResolutionThermal
Indicates the level of detail or clarity in a thermal image, typically expressed as the number of pixels or spatial resolution of the thermal sensor.
-
D.
samplingResolution
Indicates the level of detail or granularity at which data is sampled or measurements are taken in a process or system.
-
E.
telephotoCameraResolution
Indicates the image resolution capability of a device’s telephoto camera in a given 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_69f01a5d7ec88190ada2d5be7c06c35d |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_69f64fd847008190b2e0f3364ac3fedd |
completed | May 2, 2026, 7:26 p.m. |
| PD | Predicate disambiguation | batch_69f64cb0d8008190912e1430cfaf92aa |
completed | May 2, 2026, 7:12 p.m. |
Created at: April 28, 2026, 3:30 a.m.