Triple

T23186626
Position Surface form Disambiguated ID Type / Status
Subject REGN E579608 entity
Predicate hasUnderlyingCompanyTicker P33802 FINISHED
Object REGN 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: REGN | Statement: [REGN, hasUnderlyingCompanyTicker, REGN]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: REGN
Context triple: [REGN, hasUnderlyingCompanyTicker, REGN]
  • A. REGN chosen
    REGN is the stock ticker symbol for Regeneron Pharmaceuticals, a major U.S.-based biotechnology company known for developing innovative antibody-based therapies.
  • B. Remigen
    Remigen is a small Swiss municipality located in the canton of Aargau.
  • C. RGN
    RGN is the IATA airport code for Yangon International Airport, the main international gateway to Myanmar’s largest city, Yangon.
  • D. REGN-EB3
    REGN-EB3 is a monoclonal antibody cocktail developed by Regeneron to treat Ebola virus disease, shown to significantly reduce mortality in clinical trials.
  • E. Plegridy
    Plegridy is a pegylated interferon beta-1a medication used to treat relapsing forms of multiple sclerosis.
  • 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_69e245ff8000819090d12008805315b7 completed April 17, 2026, 2:38 p.m.
NER Named-entity recognition batch_69f18fd3aaa08190b9cf7afe4ee5a38d completed April 29, 2026, 4:57 a.m.
Created at: April 17, 2026, 4:05 p.m.