Triple

T19641045
Position Surface form Disambiguated ID Type / Status
Subject Louis Pasteur Middle School E471537 entity
Predicate namedAfter P63 FINISHED
Object Louis Pasteur NE NERFINISHED

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: Louis Pasteur | Statement: [Louis Pasteur Middle School, namedAfter, Louis Pasteur]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Louis Pasteur
Context triple: [Louis Pasteur Middle School, namedAfter, Louis Pasteur]
  • A. Louis Pasteur chosen
    Louis Pasteur was a pioneering French chemist and microbiologist whose work on germ theory, vaccination, and pasteurization revolutionized medicine and public health.
  • B. Jean-Baptiste Pasteur
    Jean-Baptiste Pasteur was one of the children of the renowned French chemist and microbiologist Louis Pasteur.
  • C. Camille Pasteur
    Camille Pasteur was one of the children of the renowned French chemist and microbiologist Louis Pasteur.
  • D. Alexandre Yersin
    Alexandre Yersin was a Swiss-French physician and bacteriologist best known for identifying the plague bacillus (Yersinia pestis) and contributing significantly to infectious disease research in the late 19th century.
  • E. Émile Roux
    Émile Roux was a French physician, bacteriologist, and pioneer of immunology who played a key role in developing vaccines and antitoxins, notably for diphtheria.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e511f28481909f4bc3ea9191e54a completed April 10, 2026, 11:54 a.m.
NER Named-entity recognition batch_69e6412224d481909524d7654a36d49b completed April 20, 2026, 3:07 p.m.
Created at: April 10, 2026, 1:44 p.m.