Triple

T5741490
Position Surface form Disambiguated ID Type / Status
Subject Brief Interviews with Hideous Men (film) E126623 entity
Predicate starredActor P5563 FINISHED
Object Ben Shenkman E509260 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: Ben Shenkman | Statement: [Brief Interviews with Hideous Men (film), starredActor, Ben Shenkman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ben Shenkman
Context triple: [Brief Interviews with Hideous Men (film), starredActor, Ben Shenkman]
  • A. Ben Shenkman chosen
    Ben Shenkman is an American actor known for his work in film, television, and theater, including acclaimed roles in projects like "Angels in America."
  • B. Greg Shenkman
    Greg Shenkman is a technology entrepreneur best known as a co-founder of the customer experience and contact center software company Genesys.
  • C. Dov Frohman
    Dov Frohman is an Israeli engineer and inventor best known for pioneering the EPROM (erasable programmable read-only memory) and for his leadership role at Intel Israel.
  • D. Ali Weinberg
    Ali Weinberg is an American journalist and television news producer known for her work covering politics for major U.S. news networks.
  • E. Dan Gershon
    Dan Gershon is known as the brother of American actress Gina Gershon.
  • 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_69c0083179548190b384b0bf3c08ca4d completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c0258382908190af8787feb1e5fbcd completed March 22, 2026, 5:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0a16436588190943a0b81ea9429d9 completed March 23, 2026, 2:11 a.m.
Created at: March 22, 2026, 3:48 p.m.