Triple

T1801786
Position Surface form Disambiguated ID Type / Status
Subject Finkelstein E39736 entity
Predicate hasNotableBearer P458 FINISHED
Object Louis Finkelstein E167479 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: Louis Finkelstein | Statement: [Finkelstein, hasNotableBearer, Louis Finkelstein]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Louis Finkelstein
Context triple: [Finkelstein, hasNotableBearer, Louis Finkelstein]
  • A. Louis Finkelstein chosen
    Louis Finkelstein was a prominent American Conservative rabbi and scholar who served as a long-time leader and chancellor of the Jewish Theological Seminary of America.
  • B. Irving Brecher
    Irving Brecher was an American screenwriter best known for his work on Marx Brothers comedies and classic Hollywood films of the 1930s and 1940s.
  • C. Louis Bernstein
    Louis Bernstein is the birth name of Leonard Bernstein, the renowned American composer, conductor, and pianist.
  • D. Leo Löwenthal
    Leo Löwenthal was a German sociologist and literary critic associated with the Frankfurt School, known for his analyses of mass culture, literature, and the sociology of intellectuals.
  • E. Samuel Hoffenstein
    Samuel Hoffenstein was an American screenwriter and poet best known for his witty, sophisticated scripts in Hollywood films of the 1930s and 1940s.
  • 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_69a88632aa588190ba3978fde0db5bbd completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa656c4c5481908468c6e6f9c4bfc0 completed March 6, 2026, 5:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69aef071a6588190bf45a797b4d10f8b completed March 9, 2026, 4:08 p.m.
Created at: March 4, 2026, 7:32 p.m.