Triple

T4763836
Position Surface form Disambiguated ID Type / Status
Subject Objective, Burma! E105760 entity
Predicate screenwriter P2831 FINISHED
Object Lester Cole
Lester Cole was an American screenwriter and one of the Hollywood Ten, blacklisted during the Red Scare for alleged communist affiliations.
 E467711 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: Lester Cole | Statement: [Objective, Burma!, screenwriter, Lester Cole]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lester Cole
Context triple: [Objective, Burma!, screenwriter, Lester Cole]
  • A. Lester
    Lester is a surname of Irish origin borne by various notable individuals, including the diplomat Seán Lester.
  • B. Lester
    Lester is the central character in the 2016 puzzle-platform video game "Mekazoo" (also known as "Makers" in some regions), around whom the game's story and gameplay revolve.
  • C. Lester
    Lester is a small town located in Raleigh County in the southern part of West Virginia, United States.
  • D. Lester
    Lester is the given name of Lester B. Pearson, the Canadian diplomat, Nobel Peace Prize laureate, and 14th prime minister of Canada.
  • E. Raymond Chambers
    Raymond Chambers is an American philanthropist and businessman known for his work in global health initiatives and efforts to combat malaria.
  • 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: Lester Cole
Triple: [Objective, Burma!, screenwriter, Lester Cole]
Generated description
Lester Cole was an American screenwriter and one of the Hollywood Ten, blacklisted during the Red Scare for alleged communist affiliations.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lester Cole
Target entity description: Lester Cole was an American screenwriter and one of the Hollywood Ten, blacklisted during the Red Scare for alleged communist affiliations.
  • A. Lester
    Lester is a small town located in Raleigh County in the southern part of West Virginia, United States.
  • B. Lester
    Lester is a surname of Irish origin borne by various notable individuals, including the diplomat Seán Lester.
  • C. Lester
    Lester is the central character in the 2016 puzzle-platform video game "Mekazoo" (also known as "Makers" in some regions), around whom the game's story and gameplay revolve.
  • D. Lester
    Lester is the given name of Lester B. Pearson, the Canadian diplomat, Nobel Peace Prize laureate, and 14th prime minister of Canada.
  • E. Raymond Chambers
    Raymond Chambers is an American philanthropist and businessman known for his work in global health initiatives and efforts to combat malaria.
  • 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_69bd43f14cac819081c7c69803648211 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6530f0648190b76db9964471cfeb completed March 20, 2026, 3:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69be3a87741081909380c51ba4efed92 completed March 21, 2026, 6:28 a.m.
NEDg Description generation batch_69be3d444b888190b2df7433502604ff completed March 21, 2026, 6:40 a.m.
NED2 Entity disambiguation (via description) batch_69be3dd31c648190bfdac15fb85cfec9 completed March 21, 2026, 6:42 a.m.
Created at: March 20, 2026, 1:20 p.m.