Triple

T10183349
Position Surface form Disambiguated ID Type / Status
Subject R68 E236842 entity
Predicate manufacturer P490 FINISHED
Object ANF Industrie E410189 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: ANF Industrie | Statement: [R68, manufacturer, ANF Industrie]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ANF Industrie
Context triple: [R68, manufacturer, ANF Industrie]
  • A. ANF Industrie chosen
    ANF Industrie is a French rolling stock manufacturer known for producing railway and metro vehicles, including subway cars such as the R68 for the New York City Subway.
  • B. Aunus Group
    The Aunus Group was a Finnish military formation that operated on the eastern front during World War II, particularly in the region of East Karelia.
  • C. Shao Industries
    Shao Industries is a company or corporate entity associated with and employing Liwen Shao.
  • D. Alfa Group
    Alfa Group is a major Russian privately owned investment consortium with significant interests in banking, oil and gas, telecommunications, and retail.
  • E. ANA Group
    ANA Group is a major Japanese aviation conglomerate centered around All Nippon Airways, operating passenger and cargo airlines as well as related aviation services.
  • 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_69ca84d7260c8190bfbec36762943f37 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cded3408b88190a7d981a6dcea48d9 completed April 2, 2026, 4:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69d3179b9de88190ba3beb7d6dbf7ad3 completed April 6, 2026, 2:16 a.m.
Created at: March 30, 2026, 9:12 p.m.