Triple

T3875643
Position Surface form Disambiguated ID Type / Status
Subject Venus Express E92493 entity
Predicate instrument P792 FINISHED
Object MAG
MAG is the magnetometer instrument aboard the European Space Agency’s Venus Express spacecraft, designed to measure Venus’s magnetic field and its interaction with the solar wind.
 E394670 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: MAG | Statement: [Venus Express, instrument, MAG]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: MAG
Context triple: [Venus Express, instrument, MAG]
  • A. MAG
    MAG is a major British airport operator that owns and manages several UK airports, including Manchester Airport.
  • B. MAG
    MAG is the parent company of Malaysia Airlines and related aviation businesses, overseeing the group’s airline, cargo, and aviation services operations.
  • C. MAG
    MAG is the abbreviated name used to represent Magic Gaming, the NBA 2K League affiliate of the Orlando Magic.
  • D. CMAG
    CMAG is the abbreviated name for the Commonwealth Ministerial Action Group, a body of foreign ministers that addresses serious or persistent violations of Commonwealth political values by member states.
  • E. MAG-39
    MAG-39 is a United States Marine Corps aviation unit that provides helicopter and tiltrotor support for Marine Air-Ground Task Force operations.
  • 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: MAG
Triple: [Venus Express, instrument, MAG]
Generated description
MAG is the magnetometer instrument aboard the European Space Agency’s Venus Express spacecraft, designed to measure Venus’s magnetic field and its interaction with the solar wind.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: MAG
Target entity description: MAG is the magnetometer instrument aboard the European Space Agency’s Venus Express spacecraft, designed to measure Venus’s magnetic field and its interaction with the solar wind.
  • A. MAG
    MAG is a major British airport operator that owns and manages several UK airports, including Manchester Airport.
  • B. MAG
    MAG is the abbreviated name used to represent Magic Gaming, the NBA 2K League affiliate of the Orlando Magic.
  • C. MAG
    MAG is the parent company of Malaysia Airlines and related aviation businesses, overseeing the group’s airline, cargo, and aviation services operations.
  • D. CMAG
    CMAG is the abbreviated name for the Commonwealth Ministerial Action Group, a body of foreign ministers that addresses serious or persistent violations of Commonwealth political values by member states.
  • E. MAG-39
    MAG-39 is a United States Marine Corps aviation unit that provides helicopter and tiltrotor support for Marine Air-Ground Task Force operations.
  • 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_69aed967448c819086c4b358d37b25aa completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeec706434819095e0d2b376adb548 completed March 9, 2026, 3:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5124f095881909143b624128ff569 completed March 14, 2026, 7:46 a.m.
NEDg Description generation batch_69b512f4041081908eb32ae059681afa completed March 14, 2026, 7:49 a.m.
NED2 Entity disambiguation (via description) batch_69b5137200a08190bd2a78398e03803e completed March 14, 2026, 7:51 a.m.
Created at: March 9, 2026, 3:20 p.m.