Triple

T9838021
Position Surface form Disambiguated ID Type / Status
Subject SPOT Earth observation satellites E239151 entity
Predicate developedBy P73 FINISHED
Object Société pour l’Observation de la Terre (SPOT Image)
Société pour l’Observation de la Terre (SPOT Image) is a French company that commercializes and distributes high-resolution satellite imagery and geospatial information derived from the SPOT Earth observation satellite system.
E239151 NE FINISHED

How this triple was built (4 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: Société pour l’Observation de la Terre (SPOT Image) | Statement: [SPOT Earth observation satellites, developedBy, Société pour l’Observation de la Terre (SPOT Image)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Société pour l’Observation de la Terre (SPOT Image)
Context triple: [SPOT Earth observation satellites, developedBy, Société pour l’Observation de la Terre (SPOT Image)]
  • A. SPOT Earth observation satellites
    SPOT Earth observation satellites are a series of French-led remote sensing spacecraft that provide high-resolution optical imagery of Earth for applications such as mapping, environmental monitoring, and land-use analysis.
  • B. Terra satellite
    Terra is a flagship NASA Earth observation satellite that carries multiple instruments to monitor the planet’s climate, land, oceans, and atmosphere from polar orbit.
  • C. Landsat satellites
    Landsat satellites are a series of Earth-observing spacecraft that provide long-term, continuous multispectral imagery used worldwide for environmental monitoring, land-use mapping, and resource management.
  • D. European Organisation for the Exploitation of Meteorological Satellites
    The European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) is an intergovernmental organization that develops, launches, and operates meteorological satellites to provide weather and climate data to its member states and international partners.
  • E. ALOS Earth observation satellites
    ALOS Earth observation satellites are Japanese remote-sensing spacecraft designed to collect high-resolution imagery and data for mapping, disaster monitoring, and environmental observation.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Société pour l’Observation de la Terre (SPOT Image)
Triple: [SPOT Earth observation satellites, developedBy, Société pour l’Observation de la Terre (SPOT Image)]
Generated description
Société pour l’Observation de la Terre (SPOT Image) is a French company that commercializes and distributes high-resolution satellite imagery and geospatial information derived from the SPOT Earth observation satellite system.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Société pour l’Observation de la Terre (SPOT Image)
Target entity description: Société pour l’Observation de la Terre (SPOT Image) is a French company that commercializes and distributes high-resolution satellite imagery and geospatial information derived from the SPOT Earth observation satellite system.
  • A. SPOT Earth observation satellites chosen
    SPOT Earth observation satellites are a series of French-led remote sensing spacecraft that provide high-resolution optical imagery of Earth for applications such as mapping, environmental monitoring, and land-use analysis.
  • B. Terra satellite
    Terra is a flagship NASA Earth observation satellite that carries multiple instruments to monitor the planet’s climate, land, oceans, and atmosphere from polar orbit.
  • C. Landsat satellites
    Landsat satellites are a series of Earth-observing spacecraft that provide long-term, continuous multispectral imagery used worldwide for environmental monitoring, land-use mapping, and resource management.
  • D. European Organisation for the Exploitation of Meteorological Satellites
    The European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) is an intergovernmental organization that develops, launches, and operates meteorological satellites to provide weather and climate data to its member states and international partners.
  • E. ALOS Earth observation satellites
    ALOS Earth observation satellites are Japanese remote-sensing spacecraft designed to collect high-resolution imagery and data for mapping, disaster monitoring, and environmental observation.
  • F. None of above.

Provenance (5 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_69ca84e314108190978324a4bdb959f8 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb347ff4c81908c312548a25bae71 completed April 2, 2026, 12:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69d1d5d145ac8190ad10a4328216ef54 completed April 5, 2026, 3:24 a.m.
NEDg Description generation batch_69d1d6bb23cc81909efbeccf147018e8 completed April 5, 2026, 3:27 a.m.
NED2 Entity disambiguation (via description) batch_69d1d726e58c819090135d1ff275d2d8 completed April 5, 2026, 3:29 a.m.
Created at: March 30, 2026, 8:33 p.m.