Triple

T8210822
Position Surface form Disambiguated ID Type / Status
Subject Tu Youyou E191811 entity
Predicate name P16 FINISHED
Object Tu Youyou E191811 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: Tu Youyou | Statement: [Tu Youyou, name, Tu Youyou]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tu Youyou
Context triple: [Tu Youyou, name, Tu Youyou]
  • A. Tu Youyou chosen
    Tu Youyou is a Chinese pharmaceutical chemist and Nobel laureate renowned for discovering the antimalarial drug artemisinin, which has saved millions of lives worldwide.
  • B. Shi Yigong
    Shi Yigong is a prominent Chinese structural biologist and academic leader known for his influential research on protein structures and his role in advancing higher education and scientific research in China.
  • C. Yuan T. Lee
    Yuan T. Lee is a Taiwanese chemist and Nobel laureate renowned for his pioneering work in chemical reaction dynamics.
  • D. Li Shizhen
    Li Shizhen was a renowned Ming dynasty physician and pharmacologist best known for compiling the monumental medical encyclopedia "Compendium of Materia Medica" (Bencao Gangmu).
  • E. Gertrude B. Elion
    Gertrude B. Elion was an American biochemist and pharmacologist, Nobel Prize laureate, renowned for pioneering the rational design of drugs to treat leukemia, autoimmune disorders, and organ transplant rejection.
  • 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_69ca82c8c054819087fedd9a5436b8a3 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb76dd881c8190adcbeb2f33d3295c completed March 31, 2026, 7:25 a.m.
NED1 Entity disambiguation (via context triple) batch_69ccede2e4f481908edca856038772d3 completed April 1, 2026, 10:05 a.m.
Created at: March 30, 2026, 5:44 p.m.