Triple

T2825237
Position Surface form Disambiguated ID Type / Status
Subject Yale School of Medicine E54902 entity
Predicate hasNotableFaculty P141 FINISHED
Object Jonas Salk E157143 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: Jonas Salk | Statement: [Yale School of Medicine, hasNotableFaculty, Jonas Salk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jonas Salk
Context triple: [Yale School of Medicine, hasNotableFaculty, Jonas Salk]
  • A. Jonas Salk chosen
    Jonas Salk was an American medical researcher and virologist best known for developing the first safe and effective polio vaccine.
  • B. William H. Foege
    William H. Foege is an American epidemiologist and former CDC director renowned for his pivotal role in developing the global strategy that led to the eradication of smallpox.
  • C. Karl Gajdusek
    Karl Gajdusek is an American screenwriter, producer, and showrunner known for his work on films such as "The King’s Man" and the TV series "Last Resort."
  • D. Frank Fenner
    Frank Fenner was an Australian virologist and microbiologist renowned for his pivotal role in the global eradication of smallpox and his contributions to controlling myxomatosis in rabbits.
  • E. B. B. Collip
    B. B. Collip was a Canadian biochemist best known as a key member of the team that developed insulin as a treatment for diabetes.
  • 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_69ab49e100c0819082a40cb797383243 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abde925e688190bb390d3182f8c4f0 completed March 7, 2026, 8:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69afceaf9298819093eb24a8ff0b5e02 completed March 10, 2026, 7:56 a.m.
Created at: March 6, 2026, 9:59 p.m.