Triple

T18635527
Position Surface form Disambiguated ID Type / Status
Subject Matra 530 E455535 entity
Predicate manufacturer P490 FINISHED
Object Matra NE NERFINISHED

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: Matra | Statement: [Matra 530, manufacturer, Matra]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Matra
Context triple: [Matra 530, manufacturer, Matra]
  • A. Matra chosen
    Matra is a French engineering and aerospace company known for its work in transportation systems, defense, and automotive technologies.
  • B. Fuso
    Fuso is a commercial vehicle manufacturer best known for its trucks and buses, operating as part of Daimler’s global automotive group.
  • C. Citura
    Citura is the public transport operator responsible for managing Reims’ urban transit network, including its tramway system, in northeastern France.
  • D. Sitra
    Sitra is a small island in Bahrain known for its residential communities, industrial facilities, and role in the country’s oil and gas infrastructure.
  • E. Teves
    Teves is an alternative Ashkenazi transliteration of the Hebrew month name Tevet, used in the Jewish calendar.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8d38cc7948190a55ea64e5638994e completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e54fc80b308190932303231524d372 completed April 19, 2026, 9:57 p.m.
Created at: April 10, 2026, 11:46 a.m.