Triple

T3173426
Position Surface form Disambiguated ID Type / Status
Subject Paris Métro Line 6 E66406 entity
Predicate servesStation P839 FINISHED
Object Pasteur E29652 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: Pasteur | Statement: [Paris Métro Line 6, servesStation, Pasteur]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pasteur
Context triple: [Paris Métro Line 6, servesStation, Pasteur]
  • A. Camille Pasteur
    Camille Pasteur was one of the children of the renowned French chemist and microbiologist Louis Pasteur.
  • B. Jean-Baptiste Pasteur
    Jean-Baptiste Pasteur was one of the children of the renowned French chemist and microbiologist Louis Pasteur.
  • C. Marie-Louise Pasteur
    Marie-Louise Pasteur was a daughter of the renowned French chemist and microbiologist Louis Pasteur.
  • D. 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.
  • 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 (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_69ad8586a34c8190944c63ec11a8de1a completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada66facf881908b9ec687d68ce91b completed March 8, 2026, 4:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69b235edf7708190b79605a05baf1711 completed March 12, 2026, 3:41 a.m.
Created at: March 8, 2026, 3:06 p.m.