Triple

T10923456
Position Surface form Disambiguated ID Type / Status
Subject DASA E258003 entity
Predicate successor P78 FINISHED
Object EADS E498812 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: EADS | Statement: [DASA, successor, EADS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: EADS
Context triple: [DASA, successor, EADS]
  • A. EADS chosen
    EADS (European Aeronautic Defence and Space Company) was a major European aerospace and defense corporation that later became part of Airbus Group.
  • B. Airbus
    Airbus is a major European aerospace corporation known for designing and manufacturing commercial airliners such as the A320, A330, and A380 families.
  • C. Aérospatiale
    Aérospatiale was a major French aerospace manufacturer and state-owned company that played a key role in European aviation and space projects, including as a founding partner of Airbus.
  • D. Airbus Transport International
    Airbus Transport International is a specialized cargo airline that operates Airbus Beluga aircraft to transport oversized aircraft components and other outsize freight for Airbus and its partners.
  • E. Europrop International
    Europrop International is a European aerospace consortium that designs and manufactures advanced turboprop engines for military transport aircraft, most notably the Airbus A400M.
  • 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_69d6aa864ed88190818280ab6791d065 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d7708e3fd881908da10f24a856364c completed April 9, 2026, 9:25 a.m.
NED1 Entity disambiguation (via context triple) batch_69e2172894d88190b7b27f78e9fd1521 completed April 17, 2026, 11:19 a.m.
Created at: April 8, 2026, 9:22 p.m.