Triple

T17018382
Position Surface form Disambiguated ID Type / Status
Subject The Final Girls E412879 entity
Predicate castMember P1668 FINISHED
Object Dan B. Norris
Dan B. Norris is an actor known for his role in the horror-comedy film "The Final Girls."
 E1283553 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: Dan B. Norris | Statement: [The Final Girls, castMember, Dan B. Norris]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Dan B. Norris
Context triple: [The Final Girls, castMember, Dan B. Norris]
  • A. David Norris
    David Norris is a charismatic New York politician whose fate is mysteriously manipulated by a secretive organization in the science-fiction film "The Adjustment Bureau."
  • B. Ben L. Perry
    Ben L. Perry was a screenwriter best known for his work on mid-20th-century American genre films, including the Western noir "Terror in a Texas Town."
  • C. Donald Norcross
    Donald Norcross is a Democratic U.S. Representative from New Jersey, known for his work on labor issues and advocacy for working-class families.
  • D. Paul D. Millspaugh
    Paul D. Millspaugh is an editor known for his work on the film "The Perfect Holiday."
  • E. Douglas Peters
    Douglas Peters was a Canadian economist, banker, and Liberal politician who served as a Member of Parliament and Secretary of State for International Financial Institutions in the 1990s.
  • 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: Dan B. Norris
Triple: [The Final Girls, castMember, Dan B. Norris]
Generated description
Dan B. Norris is an actor known for his role in the horror-comedy film "The Final Girls."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Dan B. Norris
Target entity description: Dan B. Norris is an actor known for his role in the horror-comedy film "The Final Girls."
  • A. David Norris
    David Norris is a charismatic New York politician whose fate is mysteriously manipulated by a secretive organization in the science-fiction film "The Adjustment Bureau."
  • B. Ben L. Perry
    Ben L. Perry was a screenwriter best known for his work on mid-20th-century American genre films, including the Western noir "Terror in a Texas Town."
  • C. Donald Norcross
    Donald Norcross is a Democratic U.S. Representative from New Jersey, known for his work on labor issues and advocacy for working-class families.
  • D. Paul D. Millspaugh
    Paul D. Millspaugh is an editor known for his work on the film "The Perfect Holiday."
  • E. Douglas Peters
    Douglas Peters was a Canadian economist, banker, and Liberal politician who served as a Member of Parliament and Secretary of State for International Financial Institutions in the 1990s.
  • 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_69d886cc4170819093deddc7b8b4b6a7 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d480a58c8190a3912d26debb4311 completed April 18, 2026, 6:59 p.m.
NED1 Entity disambiguation (via context triple) batch_6a023007da0c81908a9665d62a24b44c completed May 11, 2026, 7:37 p.m.
NEDg Description generation batch_6a023192ea9c819096bf6ed8952f21c4 completed May 11, 2026, 7:44 p.m.
NED2 Entity disambiguation (via description) batch_6a02321a9c6c8190a86ebfdcfa32f786 completed May 11, 2026, 7:46 p.m.
Created at: April 10, 2026, 5:33 a.m.