Triple

T11157683
Position Surface form Disambiguated ID Type / Status
Subject The Man from Elysian Fields E263952 entity
Predicate writer P1360 FINISHED
Object Phillip Jayson Lasker
Phillip Jayson Lasker is a screenwriter best known for penning the 2001 drama film "The Man from Elysian Fields."
 E778977 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: Phillip Jayson Lasker | Statement: [The Man from Elysian Fields, writer, Phillip Jayson Lasker]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Phillip Jayson Lasker
Context triple: [The Man from Elysian Fields, writer, Phillip Jayson Lasker]
  • A. Reuben Lasker
    Reuben Lasker was a prominent American fisheries biologist known for his influential research on fish larvae and marine ecosystems.
  • B. Edward Lasker
    Edward Lasker was an American film producer and studio executive active in Hollywood during the mid-20th century.
  • C. Lewis L. Lasker
    Lewis L. Lasker was a notable figure significant enough in his community or field to have the Lasker Rink named in his honor.
  • D. Lawrence Lasker
    Lawrence Lasker is an American film producer and screenwriter best known for his work on acclaimed dramas and science-themed films such as "Awakenings" and "WarGames."
  • E. Robert Fisher Jr.
    Robert Fisher Jr. is a film editor best known for his work on the acclaimed animated feature "Spider-Man: Into the Spider-Verse."
  • 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: Phillip Jayson Lasker
Triple: [The Man from Elysian Fields, writer, Phillip Jayson Lasker]
Generated description
Phillip Jayson Lasker is a screenwriter best known for penning the 2001 drama film "The Man from Elysian Fields."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Phillip Jayson Lasker
Target entity description: Phillip Jayson Lasker is a screenwriter best known for penning the 2001 drama film "The Man from Elysian Fields."
  • A. Reuben Lasker
    Reuben Lasker was a prominent American fisheries biologist known for his influential research on fish larvae and marine ecosystems.
  • B. Edward Lasker
    Edward Lasker was an American film producer and studio executive active in Hollywood during the mid-20th century.
  • C. Lewis L. Lasker
    Lewis L. Lasker was a notable figure significant enough in his community or field to have the Lasker Rink named in his honor.
  • D. Lawrence Lasker chosen
    Lawrence Lasker is an American film producer and screenwriter best known for his work on acclaimed dramas and science-themed films such as "Awakenings" and "WarGames."
  • E. Robert Fisher Jr.
    Robert Fisher Jr. is a film editor best known for his work on the acclaimed animated feature "Spider-Man: Into the Spider-Verse."
  • F. None of above.

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_69d6aa9ccddc8190868998c8b7beb060 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e87fe9a881909540ecc4ed9b6b9f completed April 9, 2026, 5:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69e46352e0688190924f15bc7d7ede90 completed April 19, 2026, 5:08 a.m.
NEDg Description generation batch_69e46c374ca08190a876ee68dea9b821 completed April 19, 2026, 5:46 a.m.
NED2 Entity disambiguation (via description) batch_69e4747bc02c81908f0782cf85667f3f completed April 19, 2026, 6:21 a.m.
Created at: April 8, 2026, 9:28 p.m.