Triple

T8494262
Position Surface form Disambiguated ID Type / Status
Subject Jeppson E201054 entity
Predicate hasSpellingVariant P457 FINISHED
Object Jepsen E62016 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: Jepsen | Statement: [Jeppson, hasSpellingVariant, Jepsen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jepsen
Context triple: [Jeppson, hasSpellingVariant, Jepsen]
  • A. Jepsen chosen
    Jepsen is a surname most notably associated with individuals such as display technology innovator Mary Lou Jepsen.
  • B. Percona
    Percona is an open-source database software and services company known for its performance-focused distributions and support for MySQL, MariaDB, MongoDB, and related technologies.
  • C. Crossbench
    The Crossbench is a group of independent, non-party-affiliated members in the UK House of Lords who are not aligned with any political party.
  • D. Jaspers
    Jaspers is a German surname most notably associated with the existentialist philosopher and psychiatrist Karl Jaspers.
  • E. JEP
    JEP is a leading peer-reviewed academic journal that publishes accessible, survey-style articles on a wide range of economics topics for both specialists and informed non-specialists.
  • 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_69ca831ee390819095fae73400bbfafc completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe57c01f881908cb77c8c834ac08d completed March 31, 2026, 3:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce3a5c260c8190bc7012a04363d260 completed April 2, 2026, 9:43 a.m.
Created at: March 30, 2026, 6:13 p.m.