Triple

T18711461
Position Surface form Disambiguated ID Type / Status
Subject Starman E457523 entity
Predicate screenwriter P2831 FINISHED
Object Dean Riesner 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: Dean Riesner | Statement: [Starman, screenwriter, Dean Riesner]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dean Riesner
Context triple: [Starman, screenwriter, Dean Riesner]
  • A. Dean Riesner chosen
    Dean Riesner was an American screenwriter best known for his work on films such as "Dirty Harry" and "Play Misty for Me."
  • B. Robert Dornhelm
    Robert Dornhelm is an Austrian-Romanian film and television director known for his work on historical dramas and international miniseries.
  • C. Frank Banholzer
    Frank Banholzer is a lesser-known relative of the German-American poet and theater critic Stefan Brecht, associated with the extended Brecht family.
  • D. William Diehl
    William Diehl was an American novelist best known for his gritty, suspenseful legal and crime thrillers.
  • E. Walter Leistikow
    Walter Leistikow was a German painter and graphic artist associated with German Impressionism and a leading figure in Berlin’s modern art movement around 1900.
  • 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_69d8d392aad081909fe31aa03e6e97d1 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e5671b34508190b6180f7d6ad50a58 completed April 19, 2026, 11:36 p.m.
Created at: April 10, 2026, 11:50 a.m.