Triple

T15499051
Position Surface form Disambiguated ID Type / Status
Subject Kenneth More E378899 entity
Predicate hasAutobiography P4244 FINISHED
Object Happy Go Lucky
"Happy Go Lucky" is the autobiography of British actor Kenneth More, recounting his life and career in film, theatre, and television.
 E1160100 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: Happy Go Lucky | Statement: [Kenneth More, hasAutobiography, Happy Go Lucky]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Happy Go Lucky
Context triple: [Kenneth More, hasAutobiography, Happy Go Lucky]
  • A. Lucky Me
    "Lucky Me" is a track featured on Big Sean's 2020 hip-hop album "Detroit 2."
  • B. Lucky Me
    "Lucky Me" is a 1954 Technicolor musical comedy film starring Doris Day as a superstitious chorus girl who finds romance and career opportunities in Miami.
  • C. Good Luck, Kid
    Good Luck, Kid is the second studio album by the New Zealand indie folk band Joseph, known for its rich harmonies and emotionally driven songwriting.
  • D. Lucky
    Lucky is a regional supermarket chain brand in the United States known for its neighborhood grocery stores and value-focused offerings.
  • E. Lucky
    Lucky is a recurring dog character in the animated children's series "Bluey," known as Bluey's sporty next-door neighbor and friend.
  • 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: Happy Go Lucky
Triple: [Kenneth More, hasAutobiography, Happy Go Lucky]
Generated description
"Happy Go Lucky" is the autobiography of British actor Kenneth More, recounting his life and career in film, theatre, and television.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Happy Go Lucky
Target entity description: "Happy Go Lucky" is the autobiography of British actor Kenneth More, recounting his life and career in film, theatre, and television.
  • A. Lucky Me
    "Lucky Me" is a 1954 Technicolor musical comedy film starring Doris Day as a superstitious chorus girl who finds romance and career opportunities in Miami.
  • B. Lucky Me
    "Lucky Me" is a track featured on Big Sean's 2020 hip-hop album "Detroit 2."
  • C. Good Luck, Kid
    Good Luck, Kid is the second studio album by the New Zealand indie folk band Joseph, known for its rich harmonies and emotionally driven songwriting.
  • D. Lucky
    Lucky is the protagonist of the 1993 film "Poetic Justice," portrayed by Tupac Shakur as a sensitive and complex mail carrier navigating love, grief, and self-discovery.
  • E. Lucky
    Lucky is a regional supermarket chain brand in the United States known for its neighborhood grocery stores and value-focused offerings.
  • 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_69d85cd53a7c819080f5b9042c4c199e completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e03fb0aee081909db1c54349ec8492 completed April 16, 2026, 1:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff3667a53c81908be789f99e580265 completed May 9, 2026, 1:28 p.m.
NEDg Description generation batch_69ff3744ba8c81909989864ba107b93b completed May 9, 2026, 1:31 p.m.
NED2 Entity disambiguation (via description) batch_69ff37ee94b081909309062b2d30ede5 completed May 9, 2026, 1:34 p.m.
Created at: April 10, 2026, 3:53 a.m.