Triple

T1172209
Position Surface form Disambiguated ID Type / Status
Subject Aduhelm E24938 entity
Predicate coDevelopedBy P3324 FINISHED
Object Eisai E24939 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: Eisai | Statement: [Aduhelm, coDevelopedBy, Eisai]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Eisai
Context triple: [Aduhelm, coDevelopedBy, Eisai]
  • A. Eisai chosen
    Eisai is a Japanese pharmaceutical company known for developing treatments in neurology and oncology, including Alzheimer’s disease therapies.
  • B. Novartis
    Novartis is a global Swiss-based pharmaceutical company known for developing innovative medicines across a wide range of therapeutic areas.
  • C. AstraZeneca
    AstraZeneca is a global biopharmaceutical company known for researching, developing, and manufacturing prescription medicines across areas such as oncology, cardiovascular, respiratory, and immunology.
  • D. Roche
    Roche is a major Swiss multinational healthcare company and one of the world’s leading pharmaceutical and diagnostics firms.
  • E. Sanofi
    Sanofi is a major French multinational pharmaceutical company known for developing prescription medicines, vaccines, and consumer healthcare products worldwide.
  • 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_69a494082a7c819095004f423f294a64 completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bceb3f188190b8b767380fe5986f completed March 1, 2026, 10:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac99730c408190a705ca67a6724778 completed March 7, 2026, 9:32 p.m.
Created at: March 1, 2026, 7:45 p.m.