Triple

T1168575
Position Surface form Disambiguated ID Type / Status
Subject Eli Lilly and Company E24856 entity
Predicate notableProduct P1448 FINISHED
Object Verzenio
Verzenio is a prescription cancer medication (abemaciclib) used primarily to treat certain types of hormone receptor–positive, HER2-negative breast cancer.
 E133651 NE FINISHED

How this triple was built (4 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: Verzenio | Statement: [Eli Lilly and Company, notableProduct, Verzenio]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Verzenio
Context triple: [Eli Lilly and Company, notableProduct, Verzenio]
  • A. Darzalex
    Darzalex is a monoclonal antibody drug (daratumumab) used primarily in the treatment of multiple myeloma.
  • B. Imbruvica
    Imbruvica is a targeted cancer therapy (a Bruton's tyrosine kinase inhibitor) used primarily to treat certain types of blood cancers such as mantle cell lymphoma and chronic lymphocytic leukemia.
  • C. Tecentriq
    Tecentriq is an immunotherapy cancer drug (atezolizumab) that targets the PD-L1 protein to help the immune system attack tumors in various cancers.
  • D. Anpezan
    Anpezan is a regional dialect of the Ladin language spoken in parts of the Dolomite area of northern Italy.
  • E. Vumerity
    Vumerity is an oral prescription medication used to treat relapsing forms of multiple sclerosis in adults.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Verzenio
Triple: [Eli Lilly and Company, notableProduct, Verzenio]
Generated description
Verzenio is a prescription cancer medication (abemaciclib) used primarily to treat certain types of hormone receptor–positive, HER2-negative breast cancer.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Verzenio
Target entity description: Verzenio is a prescription cancer medication (abemaciclib) used primarily to treat certain types of hormone receptor–positive, HER2-negative breast cancer.
  • A. Darzalex
    Darzalex is a monoclonal antibody drug (daratumumab) used primarily in the treatment of multiple myeloma.
  • B. Imbruvica
    Imbruvica is a targeted cancer therapy (a Bruton's tyrosine kinase inhibitor) used primarily to treat certain types of blood cancers such as mantle cell lymphoma and chronic lymphocytic leukemia.
  • C. Tecentriq
    Tecentriq is an immunotherapy cancer drug (atezolizumab) that targets the PD-L1 protein to help the immune system attack tumors in various cancers.
  • D. Anpezan
    Anpezan is a regional dialect of the Ladin language spoken in parts of the Dolomite area of northern Italy.
  • E. Vumerity
    Vumerity is an oral prescription medication used to treat relapsing forms of multiple sclerosis in adults.
  • F. None of above. chosen

Provenance (5 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_69a4bccef84481908864e819884af86c completed March 1, 2026, 10:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac668562788190ac5f8d081a46b2ee completed March 7, 2026, 5:55 p.m.
NEDg Description generation batch_69ac67a07f28819096fcd7b767e07a63 completed March 7, 2026, 6 p.m.
NED2 Entity disambiguation (via description) batch_69ac6826ef4c81909fc077bfba22b16f completed March 7, 2026, 6:02 p.m.
Created at: March 1, 2026, 7:45 p.m.