Triple

T13448550
Position Surface form Disambiguated ID Type / Status
Subject Billy Liar E320546 entity
Predicate castMember P1668 FINISHED
Object Mona Washbourne
Mona Washbourne was an English character actress known for her versatile performances in mid-20th-century British film, television, and theatre.
 E1040250 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: Mona Washbourne | Statement: [Billy Liar, castMember, Mona Washbourne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Mona Washbourne
Context triple: [Billy Liar, castMember, Mona Washbourne]
  • A. Mona Sutphen
    Mona Sutphen is an American foreign policy expert and former White House official who served in senior national security and diplomatic roles under President Barack Obama.
  • B. Georgia Welch
    Georgia Welch is best known as the wife of former U.S. Attorney General and prominent civil rights advocate Ramsey Clark.
  • C. Mona Lee Fultz
    Mona Lee Fultz is an American actress known for her work in film, television, and theater, including a role in the cult mockumentary film "True Stories."
  • D. Lucinda Franks
    Lucinda Franks was a Pulitzer Prize–winning American journalist and author known for her investigative reporting and memoirs.
  • E. Mary Woodvine
    Mary Woodvine is a British actress known for her work in television dramas and films, often appearing in character-driven and crime-related series.
  • 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: Mona Washbourne
Triple: [Billy Liar, castMember, Mona Washbourne]
Generated description
Mona Washbourne was an English character actress known for her versatile performances in mid-20th-century British film, television, and theatre.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Mona Washbourne
Target entity description: Mona Washbourne was an English character actress known for her versatile performances in mid-20th-century British film, television, and theatre.
  • A. Mona Sutphen
    Mona Sutphen is an American foreign policy expert and former White House official who served in senior national security and diplomatic roles under President Barack Obama.
  • B. Georgia Welch
    Georgia Welch is best known as the wife of former U.S. Attorney General and prominent civil rights advocate Ramsey Clark.
  • C. Mona Lee Fultz
    Mona Lee Fultz is an American actress known for her work in film, television, and theater, including a role in the cult mockumentary film "True Stories."
  • D. Lucinda Franks
    Lucinda Franks was a Pulitzer Prize–winning American journalist and author known for her investigative reporting and memoirs.
  • E. Mary Woodvine
    Mary Woodvine is a British actress known for her work in television dramas and films, often appearing in character-driven and crime-related series.
  • 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_69d80761e6cc8190a90c844589998ecc completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbaef758b08190b9aa5ec7082cd417 completed April 12, 2026, 2:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69f73999f8388190b2c578e063341178 completed May 3, 2026, 12:03 p.m.
NEDg Description generation batch_69f73af2b37481908c4d282c1335fe08 completed May 3, 2026, 12:09 p.m.
NED2 Entity disambiguation (via description) batch_69f73b959de88190959335353242031b completed May 3, 2026, 12:12 p.m.
Created at: April 9, 2026, 9:41 p.m.