Triple

T11432809
Position Surface form Disambiguated ID Type / Status
Subject Ken Ribet E270927 entity
Predicate familyName P18 FINISHED
Object Ribet E270927 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: Ribet | Statement: [Ken Ribet, familyName, Ribet]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ribet
Context triple: [Ken Ribet, familyName, Ribet]
  • A. Ken Ribet chosen
    Ken Ribet is an American mathematician known for his work in number theory, particularly his proof of the epsilon conjecture, which played a crucial role in the eventual proof of Fermat’s Last Theorem.
  • B. Victor S. Miller
    Victor S. Miller is an American mathematician and cryptographer best known for co-inventing elliptic curve cryptography, a foundational technology in modern public-key cryptography.
  • C. Andrew Wiles
    Andrew Wiles is a British mathematician renowned for proving Fermat’s Last Theorem, resolving a centuries-old problem in number theory.
  • D. Gerhard Frey
    Gerhard Frey is a German mathematician best known for his work on elliptic curves and for formulating the Frey curve, which played a key role in the eventual proof of Fermat’s Last Theorem.
  • E. Andrew Hauptman
    Andrew Hauptman is an American businessman and film producer known for his work in both entertainment and professional sports ownership.
  • 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_69d6aadeef688190874bcecd88b3dd9b completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d806c30d788190b0c939b33de89277 completed April 9, 2026, 8:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69e5d36cee548190a8215ba088bdb01a completed April 20, 2026, 7:19 a.m.
Created at: April 8, 2026, 9:35 p.m.