Triple

T4035341
Position Surface form Disambiguated ID Type / Status
Subject Fish in the Dark E83814 entity
Predicate hasCastMember P2308 FINISHED
Object Ben Shenkman
Ben Shenkman is an American actor known for his work in film, television, and theater, including acclaimed roles in projects like "Angels in America."
E509260 NE FINISHED

How this triple was built (4 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: [Fish in the Dark, hasCastMember, Ben Shenkman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ben Shenkman
Context triple: [Fish in the Dark, hasCastMember, Ben Shenkman]
  • A. Greg Shenkman
    Greg Shenkman is a technology entrepreneur best known as a co-founder of the customer experience and contact center software company Genesys.
  • B. 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.
  • C. Ali Weinberg
    Ali Weinberg is an American journalist and television news producer known for her work covering politics for major U.S. news networks.
  • D. Dan Gershon
    Dan Gershon is known as the brother of American actress Gina Gershon.
  • E. Michael Shvo
    Michael Shvo is a high-profile real estate developer and art collector known for leading luxury property projects in major global cities.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Ben Shenkman
Triple: [Fish in the Dark, hasCastMember, Ben Shenkman]
Generated description
Ben Shenkman is an American actor known for his work in film, television, and theater, including acclaimed roles in projects like "Angels in America."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Ben Shenkman
Target entity description: Ben Shenkman is an American actor known for his work in film, television, and theater, including acclaimed roles in projects like "Angels in America."
  • A. Greg Shenkman
    Greg Shenkman is a technology entrepreneur best known as a co-founder of the customer experience and contact center software company Genesys.
  • B. 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.
  • C. Ali Weinberg
    Ali Weinberg is an American journalist and television news producer known for her work covering politics for major U.S. news networks.
  • D. Dan Gershon
    Dan Gershon is known as the brother of American actress Gina Gershon.
  • E. Michael Shvo
    Michael Shvo is a high-profile real estate developer and art collector known for leading luxury property projects in major global cities.
  • F. None of above. chosen

Provenance (5 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_69aed92f7cf0819098e0539bdcc3767f completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefb132f6c8190937acd35a6a5a9e4 completed March 9, 2026, 4:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf06886d748190b346a1f4cc2b6f10 completed March 21, 2026, 8:58 p.m.
NEDg Description generation batch_69bf09e14dac8190b71f77c74463ba35 completed March 21, 2026, 9:13 p.m.
NED2 Entity disambiguation (via description) batch_69bf0a31e2f881909fd9baa9a28ae343 completed March 21, 2026, 9:14 p.m.
Created at: March 9, 2026, 3:36 p.m.