Triple

T5248777
Position Surface form Disambiguated ID Type / Status
Subject AstraZeneca E118527 entity
Predicate acquired P2511 FINISHED
Object Alexion Pharmaceuticals E505487 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: Alexion Pharmaceuticals | Statement: [AstraZeneca, acquired, Alexion Pharmaceuticals]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alexion Pharmaceuticals
Context triple: [AstraZeneca, acquired, Alexion Pharmaceuticals]
  • A. Alexion Pharmaceuticals chosen
    Alexion Pharmaceuticals is a biopharmaceutical company specializing in the development of therapies for rare and severe diseases, particularly in the field of complement biology.
  • B. Biogen
    Biogen is a major American biotechnology company known for developing therapies for neurological and neurodegenerative diseases.
  • C. Regeneron Pharmaceuticals
    Regeneron Pharmaceuticals is a leading American biotechnology company known for developing innovative antibody-based therapies for serious diseases, including eye disorders, cancer, and inflammatory conditions.
  • D. Genmab
    Genmab is a Danish biotechnology company specializing in the development of antibody-based cancer therapies.
  • E. Ariad Pharmaceuticals
    Ariad Pharmaceuticals was a biotechnology company focused on developing targeted therapies for cancer and other serious diseases.
  • 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_69bd4468aacc8190a8196f71855cdf4f completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd7b787b34819081af96de9355bb4f completed March 20, 2026, 4:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69befe68e1148190b2e3cc1f9e49dbbf completed March 21, 2026, 8:24 p.m.
Created at: March 20, 2026, 1:50 p.m.