Triple

T9807338
Position Surface form Disambiguated ID Type / Status
Subject faricimab E238184 entity
Predicate comparedWith P278 FINISHED
Object aflibercept E238303 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: aflibercept | Statement: [faricimab, comparedWith, aflibercept]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: aflibercept
Context triple: [faricimab, comparedWith, aflibercept]
  • A. aflibercept chosen
    Aflibercept is an anti-VEGF biologic drug used primarily to treat neovascular (wet) age-related macular degeneration and other retinal vascular diseases.
  • B. Lucentis
    Lucentis is a prescription anti-VEGF biologic drug used to treat several serious eye diseases, including wet age-related macular degeneration and diabetic macular edema, by inhibiting abnormal blood vessel growth in the retina.
  • C. Avastin
    Avastin is a widely used cancer drug (bevacizumab) that inhibits angiogenesis by targeting vascular endothelial growth factor (VEGF).
  • D. Vitrakvi
    Vitrakvi is a targeted cancer therapy (larotrectinib) used to treat solid tumors that have a specific NTRK gene fusion, regardless of the tumor’s location in the body.
  • E. faricimab
    Faricimab is a bispecific monoclonal antibody used to treat neovascular eye diseases such as wet age-related macular degeneration and diabetic macular edema by targeting both VEGF-A and Ang-2 pathways.
  • 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_69ca84defac48190abc1148804f184c1 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdab7ddaac8190a5584a5c863fbaa3 completed April 1, 2026, 11:34 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1cc57119881909616d835def02fc9 completed April 5, 2026, 2:43 a.m.
Created at: March 30, 2026, 8:29 p.m.