Triple

T2008292
Position Surface form Disambiguated ID Type / Status
Subject Second Chorus E43634 entity
Predicate cinematographyBy P1953 FINISHED
Object Leo Tover E82298 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: Leo Tover | Statement: [Second Chorus, cinematographyBy, Leo Tover]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Leo Tover
Context triple: [Second Chorus, cinematographyBy, Leo Tover]
  • A. Leo Tover chosen
    Leo Tover was an American cinematographer known for his work on numerous classic Hollywood films across several decades.
  • B. Leon Feldhendler
    Leon Feldhendler was a Polish Jewish resistance leader and Holocaust survivor best known for co-organizing the 1943 prisoner uprising at the Sobibor extermination camp.
  • C. Frank Basile
    Frank Basile is an American jazz baritone saxophonist and bandleader known for his work in the New York jazz scene.
  • D. Richard Leibler
    Richard Leibler was an American mathematician and statistician best known for co-developing the Kullback–Leibler divergence, a fundamental concept in information theory and statistics.
  • E. Jean Negulesco
    Jean Negulesco was a Romanian-American film director and screenwriter best known for his stylish Hollywood dramas and romances from the 1940s and 1950s.
  • 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_69a88716e9f08190946313fdc949e3cf completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abb89aca908190b8b659af65afdf6f completed March 7, 2026, 5:33 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae1fe3480c8190add171121653fc8a completed March 9, 2026, 1:18 a.m.
Created at: March 4, 2026, 7:37 p.m.