Triple

T6429324
Position Surface form Disambiguated ID Type / Status
Subject John G. Kemeny E128139 entity
Predicate familyName P18 FINISHED
Object Kemeny E592488 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: Kemeny | Statement: [John G. Kemeny, familyName, Kemeny]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kemeny
Context triple: [John G. Kemeny, familyName, Kemeny]
  • A. Kemeny chosen
    Kemeny is a surname most notably associated with figures such as mathematician and computer scientist John G. Kemeny, co-developer of the BASIC programming language and former president of Dartmouth College.
  • B. Tilden
    Tilden is a given name and surname most notably associated with several prominent American figures in politics, sports, and the arts.
  • C. Karlin
    Karlin is the professional stage name used by Danish songwriter and producer Kenneth Karlin, known for his work in pop and R&B music.
  • D. Ervin
    Ervin is a masculine given name of Germanic origin, closely related to names like Erwin and Irvin.
  • E. Evarts
    Evarts is a surname most notably associated with William M. Evarts, a prominent 19th-century American lawyer, statesman, and U.S. Secretary of State.
  • 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_69c00838de888190af2eec0b80495efa completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c06923b12081908a09543450b88c24 completed March 22, 2026, 10:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69c64bbc865c81909bf064b9253bc263 completed March 27, 2026, 9:19 a.m.
Created at: March 22, 2026, 4:44 p.m.