Triple

T18888399
Position Surface form Disambiguated ID Type / Status
Subject Big Man on Campus E462017 entity
Predicate screenwriter P2831 FINISHED
Object Allan Katz 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: Allan Katz | Statement: [Big Man on Campus, screenwriter, Allan Katz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Allan Katz
Context triple: [Big Man on Campus, screenwriter, Allan Katz]
  • A. Allan Katz chosen
    Allan Katz is a television writer and producer best known for his work on classic American sitcoms.
  • B. Don Katz
    Don Katz is an American entrepreneur and author best known as the founder of the audiobook and spoken-word entertainment company Audible.
  • C. Richard Katz
    Richard Katz is a charismatic, self-destructive indie rock musician who serves as one of the central figures in Jonathan Franzen’s novel "Freedom."
  • D. Lewis Katz
    Lewis Katz was an American businessman, philanthropist, and co-owner of the Philadelphia Inquirer known for his major charitable contributions to education and medicine.
  • E. Michael Kagan
    Michael Kagan is an Israeli technologist and entrepreneur best known as the co-founder and longtime chief technology officer of high-performance networking company Mellanox Technologies.
  • 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_69d8dcfc3430819095ee6fc0eb4c06a5 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5c478d8c481909291e7c471e5095a completed April 20, 2026, 6:15 a.m.
Created at: April 10, 2026, 11:58 a.m.