Triple

T10495372
Position Surface form Disambiguated ID Type / Status
Subject Boomers E247524 entity
Predicate stars P1956 FINISHED
Object Helen Monks
Helen Monks is a British actress, writer, and comedian known for her roles in television comedies such as Raised by Wolves and Upstart Crow.
E868827 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: Helen Monks | Statement: [Boomers, stars, Helen Monks]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Helen Monks
Context triple: [Boomers, stars, Helen Monks]
  • A. Helen Humes
    Helen Humes was an American jazz and blues singer known for her work with Count Basie’s orchestra and her versatile, swinging vocal style.
  • B. Helen McDougall
    Helen McDougall, better known by her stage name Helen Mack, was an American actress who appeared in films, radio, and early television during the 1930s and 1940s.
  • C. Helen Melland
    Helen Melland was the wife of British Prime Minister Herbert Henry Asquith and a member of the English upper-middle class in the late 19th century.
  • D. Helen Davies
    Helen Davies was the first wife of American actor George Peppard, with whom she was married in the 1950s and early 1960s.
  • E. Helen Chappel
    Helen Chappel is a central character on the sitcom "Wings," known as the sharp-tongued, ambitious airport lunch-counter worker and aspiring cellist.
  • 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: Helen Monks
Triple: [Boomers, stars, Helen Monks]
Generated description
Helen Monks is a British actress, writer, and comedian known for her roles in television comedies such as Raised by Wolves and Upstart Crow.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Helen Monks
Target entity description: Helen Monks is a British actress, writer, and comedian known for her roles in television comedies such as Raised by Wolves and Upstart Crow.
  • A. Helen Humes
    Helen Humes was an American jazz and blues singer known for her work with Count Basie’s orchestra and her versatile, swinging vocal style.
  • B. Helen McDougall
    Helen McDougall, better known by her stage name Helen Mack, was an American actress who appeared in films, radio, and early television during the 1930s and 1940s.
  • C. Helen Melland
    Helen Melland was the wife of British Prime Minister Herbert Henry Asquith and a member of the English upper-middle class in the late 19th century.
  • D. Helen Davies
    Helen Davies was the first wife of American actor George Peppard, with whom she was married in the 1950s and early 1960s.
  • E. Helen Chappel
    Helen Chappel is a central character on the sitcom "Wings," known as the sharp-tongued, ambitious airport lunch-counter worker and aspiring cellist.
  • 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_69d381c309b88190af78aa681cf6a4c2 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d5098be488819083d614f528cd82fb completed April 7, 2026, 1:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69d90dd040f48190a645ebd131f9205c completed April 10, 2026, 2:48 p.m.
NEDg Description generation batch_69d911dd4198819089585462af6b5ef5 completed April 10, 2026, 3:06 p.m.
NED2 Entity disambiguation (via description) batch_69d9126254408190a79ea571649416f6 completed April 10, 2026, 3:08 p.m.
Created at: April 6, 2026, 12:24 p.m.