Triple

T8499431
Position Surface form Disambiguated ID Type / Status
Subject Shining Through (1992 film) E201177 entity
Predicate producer P490 FINISHED
Object Howard Rosenman E430139 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: Howard Rosenman | Statement: [Shining Through (1992 film), producer, Howard Rosenman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Howard Rosenman
Context triple: [Shining Through (1992 film), producer, Howard Rosenman]
  • A. Howard Rosenman chosen
    Howard Rosenman is an American film producer known for his work on popular Hollywood movies and for helping bring LGBTQ themes into mainstream cinema.
  • B. Jay O. Rothman
    Jay O. Rothman is an American attorney and academic leader who serves as president of the University of Wisconsin System.
  • C. Howard Roseman
    Howard Roseman is an American football executive best known as the longtime general manager and key roster architect of the NFL’s Philadelphia Eagles.
  • D. Hugh Howard Rosenberg
    Hugh Howard Rosenberg is the son of American actress Marg Helgenberger and her former husband, actor Alan Rosenberg.
  • E. Howard Klausner
    Howard Klausner is an American screenwriter best known for co-writing the Clint Eastwood film "Space Cowboys" and working on various other feature and television projects.
  • 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_69ca831fe47c8190b5c57b456d2aefa0 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe5984d7481908c41c57bef9cf254 completed March 31, 2026, 3:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69d14ba9a9a8819086d7b5255b0af3e5 completed April 4, 2026, 5:34 p.m.
Created at: March 30, 2026, 6:14 p.m.