Triple

T17198669
Position Surface form Disambiguated ID Type / Status
Subject Walter Bodmer E417418 entity
Predicate name P16 FINISHED
Object Walter Bodmer E417418 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: Walter Bodmer | Statement: [Walter Bodmer, name, Walter Bodmer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Walter Bodmer
Context triple: [Walter Bodmer, name, Walter Bodmer]
  • A. Walter Bodmer chosen
    Walter Bodmer is a prominent British human geneticist and immunologist known for his influential work on the genetics of human populations and cancer.
  • B. Leopold Sanger
    Leopold Sanger is a notable member of the Sanger family, recognized for his prominence within this historically significant lineage.
  • C. Laurence Jackson Hyman
    Laurence Jackson Hyman is an American editor and writer best known for preserving and promoting the work and legacy of his mother, the author Shirley Jackson.
  • D. Martin F. Semmelhack
    Martin F. Semmelhack is an American organic chemist known for his contributions to synthetic methodology and his long career as a professor at Princeton University.
  • E. Herbert Edelman
    Herbert Edelman was an American character actor best known for his Emmy-nominated role as Stan Zbornak on the television sitcom "The Golden Girls."
  • 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_69d886d6ba8c819093215917b3d01689 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e42daca29081909837494d8d516634 completed April 19, 2026, 1:19 a.m.
NED1 Entity disambiguation (via context triple) batch_6a015fd7ef048190b0828ec6ea0e119c completed May 11, 2026, 4:49 a.m.
Created at: April 10, 2026, 5:38 a.m.