Triple

T16431906
Position Surface form Disambiguated ID Type / Status
Subject Mars Environmental Dynamics Analyzer E399088 entity
Predicate abbreviation P43 FINISHED
Object MEDA E88915 NE 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: MEDA | Statement: [Mars Environmental Dynamics Analyzer, abbreviation, MEDA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MEDA
Context triple: [Mars Environmental Dynamics Analyzer, abbreviation, MEDA]
  • A. MEDA chosen
    MEDA is a suite of environmental sensors on NASA's Perseverance rover that measures Martian weather and atmospheric conditions.
  • B. Mede
    The Medes were an ancient Iranian people who inhabited the region of Media in northwestern Iran and played a key role in the downfall of the Assyrian Empire.
  • C. MaMaMedia
    MaMaMedia is an early internet company focused on providing educational, interactive online experiences for children.
  • D. Mediasch
    Mediasch is the German name for Mediaș, a historic Transylvanian town in present-day Romania known for its medieval architecture and fortified churches.
  • E. MDE
    MDE is the IATA airport code for José María Córdova International Airport, the main international gateway serving Medellín, Colombia.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69d87f2b9024819085c20e52de95d583 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e32b9dffe48190a23852f828af55d8 completed April 18, 2026, 6:58 a.m.
NED1 Entity disambiguation (via context triple) batch_6a004584fa508190a85b1f79ecf9c258 completed May 10, 2026, 8:44 a.m.
Created at: April 10, 2026, 5:10 a.m.