Triple

T2997648
Position Surface form Disambiguated ID Type / Status
Subject Magellan spacecraft E81108 entity
Predicate surfaceResolution P33105 FINISHED
Object radar images with resolution as fine as 100–300 meters 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: radar images with resolution as fine as 100–300 meters | Statement: [Magellan spacecraft, surfaceResolution, radar images with resolution as fine as 100–300 meters]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: surfaceResolution
Context triple: [Magellan spacecraft, surfaceResolution, radar images with resolution as fine as 100–300 meters]
  • A. sensorResolution
    Indicates the level of detail or precision with which a sensor can measure or distinguish changes in the observed quantity or environment.
  • B. typicalResolution chosen
    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.
  • C. displayResolution
    Indicates the relationship specifying the width and height dimensions at which visual content is rendered or shown on a display.
  • D. mainResolution
    Indicates that one resolution is the primary or most important resolution associated with a given context or entity.
  • E. pixelScale
    Indicates the ratio or conversion factor between pixel units and real-world or coordinate-space units in a representation or image.
  • 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_69ad8b187fc8819085914d3c9ea3142d completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad99f612148190a5a565ba2ecc4fc0 completed March 8, 2026, 3:47 p.m.
PD Predicate disambiguation batch_69ad9615fefc8190ad96da92519cb7a3 completed March 8, 2026, 3:30 p.m.
Created at: March 8, 2026, 2:59 p.m.