Triple

T20744163
Position Surface form Disambiguated ID Type / Status
Subject Peter’s Friends E510525 entity
Predicate cinematographyBy P1953 FINISHED
Object Roger Lanser 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: Roger Lanser | Statement: [Peter’s Friends, cinematographyBy, Roger Lanser]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Roger Lanser
Context triple: [Peter’s Friends, cinematographyBy, Roger Lanser]
  • A. Roger Lanser chosen
    Roger Lanser is an Australian cinematographer known for his work on feature films and television, including Kenneth Branagh’s 1993 adaptation of "Much Ado About Nothing."
  • B. Roland Winters
    Roland Winters was an American character actor best known for playing detective Charlie Chan in a series of late-1940s films and for numerous supporting roles in mid-20th-century cinema.
  • C. Roy Hartle
    Roy Hartle was an English footballer best known as a long-serving full-back for Bolton Wanderers during the 1950s and 1960s.
  • D. Mario Schlosser
    Mario Schlosser is a German-born entrepreneur best known as the co-founder and former CEO of the technology-driven health insurance company Oscar Health.
  • E. Roland Wolf
    Roland Wolf is a writer best known for his work on the play "The Mercy Seat."
  • 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_69e0b4c845e88190b4c5f3ae79291182 completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c21197088190951a4c4a7e765891 completed April 21, 2026, 12:17 a.m.
Created at: April 16, 2026, 12:33 p.m.