Triple

T22759397
Position Surface form Disambiguated ID Type / Status
Subject The Return of the Pink Panther E562941 entity
Predicate screenwriter P2831 FINISHED
Object Tom Waldman
Tom Waldman was an American screenwriter best known for his work on comedy films and television, including contributions to the Pink Panther series.
 E1552845 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: Tom Waldman | Statement: [The Return of the Pink Panther, screenwriter, Tom Waldman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tom Waldman
Context triple: [The Return of the Pink Panther, screenwriter, Tom Waldman]
  • A. Tom Waldman
    Tom Waldman is an author and writer known for his work on the book "High Time."
  • B. Jeff Weltman
    Jeff Weltman is a basketball executive who serves as the top front-office decision-maker for the NBA’s Orlando Magic.
  • C. Jay Wadley
    Jay Wadley is an American composer known for his evocative film scores and work on independent and arthouse cinema.
  • D. Ed Vargo
    Ed Vargo was a prominent Major League Baseball umpire who worked in the National League for over two decades and officiated multiple World Series and All-Star Games.
  • E. John Layman
    John Layman is an American comic book writer best known as the co-creator and writer of the acclaimed series "Chew."
  • 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: Tom Waldman
Triple: [The Return of the Pink Panther, screenwriter, Tom Waldman]
Generated description
Tom Waldman was an American screenwriter best known for his work on comedy films and television, including contributions to the Pink Panther series.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tom Waldman
Target entity description: Tom Waldman was an American screenwriter best known for his work on comedy films and television, including contributions to the Pink Panther series.
  • A. Tom Waldman
    Tom Waldman is an author and writer known for his work on the book "High Time."
  • B. Jeff Weltman
    Jeff Weltman is a basketball executive who serves as the top front-office decision-maker for the NBA’s Orlando Magic.
  • C. Jay Wadley
    Jay Wadley is an American composer known for his evocative film scores and work on independent and arthouse cinema.
  • D. Ed Vargo
    Ed Vargo was a prominent Major League Baseball umpire who worked in the National League for over two decades and officiated multiple World Series and All-Star Games.
  • E. John Layman
    John Layman is an American comic book writer best known as the co-creator and writer of the acclaimed series "Chew."
  • 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_69e24552e11c81909c2d61578a558bd7 completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f17a7b4fe88190b1da25b78f046d13 completed April 29, 2026, 3:26 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0b981716888190b86a60cd134ee6eb completed May 18, 2026, 10:52 p.m.
NEDg Description generation batch_6a0b9903c4488190943f4fd15b17bc70 completed May 18, 2026, 10:56 p.m.
NED2 Entity disambiguation (via description) batch_6a0b99b87e4881909142c296be1c9bff completed May 18, 2026, 10:59 p.m.
Created at: April 17, 2026, 3:25 p.m.