Triple

T4366917
Position Surface form Disambiguated ID Type / Status
Subject Ira Eisenstein E98797 entity
Predicate name P16 FINISHED
Object Ira Eisenstein E98797 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: Ira Eisenstein | Statement: [Ira Eisenstein, name, Ira Eisenstein]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ira Eisenstein
Context triple: [Ira Eisenstein, name, Ira Eisenstein]
  • A. Ira Eisenstein chosen
    Ira Eisenstein was an American rabbi and theologian who helped found and shape Reconstructionist Judaism as a distinct modern Jewish movement.
  • B. Ira Shor
    Ira Shor is an American educator and critical pedagogue known for advancing radical, student-centered approaches to teaching and learning inspired by Paulo Freire’s theories.
  • C. Ira Hirschmann
    Ira Hirschmann was an American businessman and diplomat best known for his World War II efforts to rescue Jews from the Holocaust and his later work in international affairs.
  • D. 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.
  • E. Leo Salkin
    Leo Salkin was an American animator, writer, and storyboard artist known for his work on mid-20th-century animated films and shorts.
  • 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_69b3454db3708190aeafd814413c4c3d completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b35201be7081908808e81634060f95 completed March 12, 2026, 11:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf32f31ecc81909cb29b762481b08e completed March 22, 2026, 12:08 a.m.
Created at: March 12, 2026, 11:17 p.m.