Triple

T6064893
Position Surface form Disambiguated ID Type / Status
Subject Mounjaro E135131 entity
Predicate hasPharmacologicalClass P24600 FINISHED
Object dual GIP and GLP-1 receptor agonist LITERAL 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: dual GIP and GLP-1 receptor agonist | Statement: [Mounjaro, hasPharmacologicalClass, dual GIP and GLP-1 receptor agonist]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasPharmacologicalClass
Context triple: [Mounjaro, hasPharmacologicalClass, dual GIP and GLP-1 receptor agonist]
  • A. hasPharmacologicClass chosen
    Indicates that a drug or medicinal product belongs to a specific pharmacologic class based on its mechanism of action or therapeutic effect.
  • B. drugClass
    Indicates that one entity is classified as a particular pharmacological or therapeutic category of drugs in relation to another entity.
  • C. hasChemicalClass
    Indicates that an entity belongs to, or is categorized under, a particular chemical class based on its structural or compositional characteristics.
  • D. protectedDrugClassesInclude
    Indicates that the specified set of protected drug classes includes the referenced drug class or classes.
  • E. hasPharmacologicalEffect
    Indicates that one entity produces a specific pharmacological effect or action on another entity.
  • F. None of above.

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_69c00878d06881909ee78e88913bf890 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c05723c91c819090b4d4672e72f9f3 completed March 22, 2026, 8:54 p.m.
PD Predicate disambiguation batch_69c049f031408190b08b2766237c5dd0 completed March 22, 2026, 7:58 p.m.
Created at: March 22, 2026, 4:10 p.m.