Triple

T4559736
Position Surface form Disambiguated ID Type / Status
Subject The Company Men E120563 entity
Predicate producer P490 FINISHED
Object Claire Rudnick Polstein
Claire Rudnick Polstein is a film producer best known for her work on the drama feature "The Company Men."
E515892 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: Claire Rudnick Polstein | Statement: [The Company Men, producer, Claire Rudnick Polstein]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Claire Rudnick Polstein
Context triple: [The Company Men, producer, Claire Rudnick Polstein]
  • A. Janet Margolin
    Janet Margolin was an American film and television actress best known for her roles in movies such as "David and Lisa" and Woody Allen's "Annie Hall."
  • B. Claudia Finkelstein
    Claudia Finkelstein is a physician and academic known for her work in internal medicine and physician well-being.
  • C. Elissa Durwood Grodin
    Elissa Durwood Grodin is an American author known for writing mystery novels and children's books.
  • D. Joyce Piven
    Joyce Piven is an American acting teacher, director, and co-founder of the Piven Theatre Workshop, known for training numerous prominent actors including her son Jeremy Piven.
  • E. June Preisser
    June Preisser was an American film actress and dancer best known for her energetic supporting roles in 1930s and 1940s Hollywood musicals, often playing peppy, acrobatic teenagers.
  • 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: Claire Rudnick Polstein
Triple: [The Company Men, producer, Claire Rudnick Polstein]
Generated description
Claire Rudnick Polstein is a film producer best known for her work on the drama feature "The Company Men."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Claire Rudnick Polstein
Target entity description: Claire Rudnick Polstein is a film producer best known for her work on the drama feature "The Company Men."
  • A. Janet Margolin
    Janet Margolin was an American film and television actress best known for her roles in movies such as "David and Lisa" and Woody Allen's "Annie Hall."
  • B. Claudia Finkelstein
    Claudia Finkelstein is a physician and academic known for her work in internal medicine and physician well-being.
  • C. Elissa Durwood Grodin
    Elissa Durwood Grodin is an American author known for writing mystery novels and children's books.
  • D. Joyce Piven
    Joyce Piven is an American acting teacher, director, and co-founder of the Piven Theatre Workshop, known for training numerous prominent actors including her son Jeremy Piven.
  • E. June Preisser
    June Preisser was an American film actress and dancer best known for her energetic supporting roles in 1930s and 1940s Hollywood musicals, often playing peppy, acrobatic teenagers.
  • 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_69bd4636f1648190a701445c2fcd9c17 completed March 20, 2026, 1:05 p.m.
NER Named-entity recognition batch_69bd582b871c8190be0b70c76d639000 completed March 20, 2026, 2:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf28ea49588190bf1bc4cb3ca4dcee completed March 21, 2026, 11:25 p.m.
NEDg Description generation batch_69bf2ad1b7e0819096b1ea7fc55401f2 completed March 21, 2026, 11:33 p.m.
NED2 Entity disambiguation (via description) batch_69bf2b65903c8190a34d77b11dd1fa87 completed March 21, 2026, 11:36 p.m.
Created at: March 20, 2026, 1:09 p.m.