Triple

T10524049
Position Surface form Disambiguated ID Type / Status
Subject Betty Blue E248249 entity
Predicate mainCharacter P1183 FINISHED
Object Betty
Betty is the troubled, passionate young woman at the center of the French cult film "Betty Blue," whose intense love affair and psychological unraveling drive the story.
E869316 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: Betty | Statement: [Betty Blue, mainCharacter, Betty]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Betty
Context triple: [Betty Blue, mainCharacter, Betty]
  • A. Betty
    Betty is the childhood nickname of Elizabeth Parris, the young girl whose strange afflictions helped spark the Salem witch trials in 1692.
  • B. Betty
    Betty is a minor character in Enid Blyton’s "Malory Towers" series, known as a lively and mischievous schoolgirl at the boarding school.
  • C. Betty
    Betty is the young, resourceful heroine of the children's story "Betty's Bright Idea," known for her cleverness and problem-solving nature.
  • D. Betty
    "Betty" is a notable work by the artist Helmet, recognized as part of their influential contribution to alternative metal music.
  • E. Betty
    "Betty" is the Allied reporting name for the Mitsubishi G4M, a Japanese World War II twin-engine land-based bomber known for its long range and vulnerability due to lack of armor and self-sealing fuel tanks.
  • 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: Betty
Triple: [Betty Blue, mainCharacter, Betty]
Generated description
Betty is the troubled, passionate young woman at the center of the French cult film "Betty Blue," whose intense love affair and psychological unraveling drive the story.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Betty
Target entity description: Betty is the troubled, passionate young woman at the center of the French cult film "Betty Blue," whose intense love affair and psychological unraveling drive the story.
  • A. Betty
    Betty is a minor character in Enid Blyton’s "Malory Towers" series, known as a lively and mischievous schoolgirl at the boarding school.
  • B. Betty
    Betty is the young, resourceful heroine of the children's story "Betty's Bright Idea," known for her cleverness and problem-solving nature.
  • C. Betty
    Betty is the childhood nickname of Elizabeth Parris, the young girl whose strange afflictions helped spark the Salem witch trials in 1692.
  • D. Betty
    Betty is the birth name of iconic American actress Lauren Bacall, a legendary figure of Hollywood's Golden Age.
  • E. Betty
    Betty is the familiar nickname of Betty Ford, the former First Lady of the United States and founder of the Betty Ford Center for substance abuse treatment.
  • 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_69d381c5c7448190bec34bee7ec72bac completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d509e155b08190996325bf484ec55d completed April 7, 2026, 1:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69d90e1c73208190aa3d3e30aa4482ac completed April 10, 2026, 2:50 p.m.
NEDg Description generation batch_69d9107e8b94819086ebba1675a0db54 completed April 10, 2026, 3 p.m.
NED2 Entity disambiguation (via description) batch_69d911a16b1481909197b00c30de48c4 completed April 10, 2026, 3:05 p.m.
Created at: April 6, 2026, 12:29 p.m.