Triple

T14485807
Position Surface form Disambiguated ID Type / Status
Subject SCALP Naval E359225 entity
Predicate hasManufacturer P4022 FINISHED
Object MBDA France E411800 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: MBDA France | Statement: [SCALP Naval, hasManufacturer, MBDA France]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MBDA France
Context triple: [SCALP Naval, hasManufacturer, MBDA France]
  • A. MBDA France chosen
    MBDA France is a major European defense company specializing in the design and production of advanced missile systems and related technologies.
  • B. MBDA Germany
    MBDA Germany is a defense company specializing in the development and production of advanced missile systems and guided weapons for military applications.
  • C. MBDA
    MBDA is a U.S. federal agency dedicated to promoting the growth and competitiveness of minority-owned businesses through programs, services, and advocacy.
  • D. MBDA
    MBDA is a leading European multinational developer and manufacturer of missile systems and related defense technologies.
  • E. MBDA Italy
    MBDA Italy is the Italian branch of the European missile systems company MBDA, specializing in the design and production of advanced missile and air-defense technologies.
  • 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_69d8279740308190af9df93a3af8592e completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de924ee0f08190baf68318b41fa64d completed April 14, 2026, 7:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd7a3e32fc8190822aeb633b60af6b completed May 8, 2026, 5:53 a.m.
Created at: April 10, 2026, 1:20 a.m.