Triple

T3093691
Position Surface form Disambiguated ID Type / Status
Subject Louis Néel E64541 entity
Predicate employer P7 FINISHED
Object CNRS E54266 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: CNRS | Statement: [Louis Néel, employer, CNRS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: CNRS
Context triple: [Louis Néel, employer, CNRS]
  • A. Centre National de la Recherche Scientifique chosen
    The Centre National de la Recherche Scientifique (CNRS) is France’s largest governmental research organization, renowned for its multidisciplinary scientific research across fields ranging from physics and biology to the humanities.
  • B. INSERM
    INSERM is France’s national public research institute dedicated to human health and medical research.
  • C. Institut des Hautes Études Scientifiques
    The Institut des Hautes Études Scientifiques is a prestigious French research institute renowned for its fundamental work in mathematics and theoretical physics.
  • D. INRIA
    INRIA is the French national research institute dedicated to computer science and applied mathematics, known for its leading contributions to digital science and technology.
  • E. Académie des Sciences
    The Académie des Sciences is a prestigious French scientific institution founded in the 17th century that has played a central role in the development and promotion of science in France and internationally.
  • 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_69ad857c97d88190b26f9b1c90839c77 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada23876a4819095bfc28640d8c200 completed March 8, 2026, 4:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69b20370aba48190a31ec25bca0a4727 completed March 12, 2026, 12:06 a.m.
Created at: March 8, 2026, 3:03 p.m.