Triple

T9695522
Position Surface form Disambiguated ID Type / Status
Subject Frank Grillo E234639 entity
Predicate givenName P17 FINISHED
Object Frank
Frank is the given name of American actor Frank Grillo, known for his roles in action and thriller films such as "The Purge" series and "Captain America: The Winter Soldier."
E815729 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: Frank | Statement: [Frank Grillo, givenName, Frank]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Frank
Context triple: [Frank Grillo, givenName, Frank]
  • A. Frank
    Frank is a key supporting character in the post-apocalyptic horror film "28 Days Later," known as a protective father trying to keep his daughter safe amid a devastating viral outbreak in London.
  • B. Frank
    Frank is the given name of Frank Abagnale Jr., the infamous former con artist whose life inspired the film "Catch Me If You Can."
  • C. Frank
    Frank is the given name of British screenwriter and children's author Frank Cottrell-Boyce.
  • D. Frank
    Frank is the given name of British former professional heavyweight boxer Frank Bruno, a popular sports figure especially known in the UK.
  • E. Frank
    Frank is an alternate given name of longtime Republican U.S. Congressman Jim Sensenbrenner, who represented a Wisconsin district in the House of Representatives for four decades.
  • 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: Frank
Triple: [Frank Grillo, givenName, Frank]
Generated description
Frank is the given name of American actor Frank Grillo, known for his roles in action and thriller films such as "The Purge" series and "Captain America: The Winter Soldier."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Frank
Target entity description: Frank is the given name of American actor Frank Grillo, known for his roles in action and thriller films such as "The Purge" series and "Captain America: The Winter Soldier."
  • A. Frank
    Frank is the given name of filmmaker Frank Darabont, the acclaimed director and screenwriter known for works such as The Shawshank Redemption and The Green Mile.
  • B. Frank
    Frank is the given name of the American comic book writer, artist, and film director Frank Miller, known for works like "The Dark Knight Returns," "Sin City," and "300."
  • C. Frank
    Frank is the given name of Frank Oz, the renowned puppeteer, actor, and director best known for his work with the Muppets and on Star Wars.
  • D. Frank
    Frank is the given name of Frank País, a prominent Cuban revolutionary leader active during the Cuban Revolution.
  • E. Frank
    Frank is the given name of Frank Lampard, the renowned English former professional footballer and manager.
  • 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_69ca84cb580c8190a7e5f4b3bcdaf2a4 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cd9d366c488190bc153c68fef197c2 completed April 1, 2026, 10:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1911427d48190855506ab61f8a2ce completed April 4, 2026, 10:30 p.m.
NEDg Description generation batch_69d193a5cdac8190b84564f397d00124 completed April 4, 2026, 10:41 p.m.
NED2 Entity disambiguation (via description) batch_69d19457c6488190a7bc72e1a27c088a completed April 4, 2026, 10:44 p.m.
Created at: March 30, 2026, 8:17 p.m.