Triple

T19378683
Position Surface form Disambiguated ID Type / Status
Subject Michael Blumenthal E484737 entity
Predicate familyName P18 FINISHED
Object Blumenthal NE NERFINISHED

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: Blumenthal | Statement: [Michael Blumenthal, familyName, Blumenthal]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Blumenthal
Context triple: [Michael Blumenthal, familyName, Blumenthal]
  • A. Blumenthal chosen
    Blumenthal is a German-origin surname borne by various notable individuals in fields such as politics, academia, and the arts.
  • B. Richard Blumenthal
    Richard Blumenthal is a longtime Democratic politician and former Connecticut attorney general who has served as a United States senator from Connecticut since 2011.
  • C. Michael Blumenthal
    Michael Blumenthal is a German-born American economist, businessman, and former U.S. Secretary of the Treasury who later served as director of the Jewish Museum Berlin.
  • D. Leahy
    Leahy is a surname of Irish origin borne by various notable individuals in fields such as politics, music, and public service.
  • E. Eugene Reynolds Blumenthal
    Eugene Reynolds Blumenthal, better known as Gene Reynolds, was an American actor, director, producer, and writer best known for co-creating and producing the acclaimed television series M*A*S*H.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e8d460d88190abf0591c5c9d2b0c completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e61a5dc3048190830b55c8ca02e624 completed April 20, 2026, 12:21 p.m.
Created at: April 10, 2026, 1:35 p.m.