Triple

T8378570
Position Surface form Disambiguated ID Type / Status
Subject Polar Operational Environmental Satellites E197634 entity
Predicate instrument P792 FINISHED
Object SEM
SEM is a space-based sensor used on weather and environmental satellites to monitor the flux of energetic charged particles in Earth’s near-space environment.
 E729836 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: SEM | Statement: [Polar Operational Environmental Satellites, instrument, SEM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: SEM
Context triple: [Polar Operational Environmental Satellites, instrument, SEM]
  • A. SEMAL
    SEMAL is the UN/LOCODE designation for the port and transport location associated with Lake Mälaren in Sweden.
  • B. SEP
    SEP is the Mexican federal government department responsible for overseeing and regulating the national education system.
  • C. SEP
    SEP is the commonly used abbreviation for Sociedade Esportiva Palmeiras, one of Brazil’s most successful and popular football clubs.
  • D. SES
    SES is the abbreviation for the Senior Executive Service, the corps of top-level civilian managers and executives in the U.S. federal government.
  • E. SES
    SES is the commonly used abbreviation for St Edward's School, a co-educational independent boarding and day school in Oxford, England.
  • 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: SEM
Triple: [Polar Operational Environmental Satellites, instrument, SEM]
Generated description
SEM is a space-based sensor used on weather and environmental satellites to monitor the flux of energetic charged particles in Earth’s near-space environment.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: SEM
Target entity description: SEM is a space-based sensor used on weather and environmental satellites to monitor the flux of energetic charged particles in Earth’s near-space environment.
  • A. SEMAL
    SEMAL is the UN/LOCODE designation for the port and transport location associated with Lake Mälaren in Sweden.
  • B. SEP
    SEP is the Mexican federal government department responsible for overseeing and regulating the national education system.
  • C. SEP
    SEP is the commonly used abbreviation for Sociedade Esportiva Palmeiras, one of Brazil’s most successful and popular football clubs.
  • D. SES
    SES is the abbreviation for the Senior Executive Service, the corps of top-level civilian managers and executives in the U.S. federal government.
  • E. SES
    SES is the commonly used abbreviation for St Edward's School, a co-educational independent boarding and day school in Oxford, England.
  • F. None of above. chosen

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_69ca82f64c188190af4e1608036b865d completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb80c229708190b813f5e7e44e10d4 completed March 31, 2026, 8:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69cde7fa87908190a504f8aaae125a7a completed April 2, 2026, 3:52 a.m.
NEDg Description generation batch_69cdebf944008190b7e758ac59257e22 completed April 2, 2026, 4:09 a.m.
NED2 Entity disambiguation (via description) batch_69cdeccedf4081909cab853ee1ff1b82 completed April 2, 2026, 4:13 a.m.
Created at: March 30, 2026, 6:02 p.m.