Triple

T17871518
Position Surface form Disambiguated ID Type / Status
Subject Givlaari E446846 entity
Predicate hasRegulatoryApproval P24602 FINISHED
Object EMA 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: EMA | Statement: [Givlaari, hasRegulatoryApproval, EMA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: EMA
Context triple: [Givlaari, hasRegulatoryApproval, EMA]
  • A. EMA chosen
    EMA is the European Union’s regulatory authority responsible for the scientific evaluation, supervision, and safety monitoring of medicines.
  • B. EMA
    EMA is the three-letter IATA airport code for East Midlands Airport in England, which serves the East Midlands region with domestic and international flights.
  • C. EMA
    EMA is the abbreviated name for the Joint Staff headquarters that oversees and coordinates the operations of the French Armed Forces.
  • D. EMA
    EMA is the acronym for the Spanish Navy Staff, the central command body responsible for directing and managing Spain’s naval forces.
  • E. Em
    Em is a common shortened form of the given name Emma, often used as an informal nickname.
  • 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_69d8b9f4c22c819093c2680434472894 completed April 10, 2026, 8:51 a.m.
NER Named-entity recognition batch_69e49aa30ff8819090c51c1d7767e952 completed April 19, 2026, 9:04 a.m.
Created at: April 10, 2026, 10:18 a.m.