Triple

T10368162
Position Surface form Disambiguated ID Type / Status
Subject Bad Santa E244308 entity
Predicate mainCharacter P1183 FINISHED
Object Sue
Sue is a character from the dark comedy film "Bad Santa," known as the love interest of the main antihero, Willie T. Soke.
E858762 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: Sue | Statement: [Bad Santa, mainCharacter, Sue]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sue
Context triple: [Bad Santa, mainCharacter, Sue]
  • A. Sue
    Sue is the tough, resilient male protagonist of the humorous country song "A Boy Named Sue," whose life is shaped by the hardships caused by his traditionally feminine name.
  • B. Sue
    Sue is the given name of Sue Storm, the Invisible Woman and a central member of Marvel’s superhero team the Fantastic Four.
  • C. Suzie
    Suzie is a brilliant, tech-savvy girl from Stranger Things who helps Dustin Henderson and his friends by providing crucial scientific and hacking assistance.
  • D. Suzanne
    Suzanne is a central character in Steve Martin’s play "Picasso at the Lapin Agile," representing a young woman entangled romantically with both Picasso and other men in the bohemian Parisian setting.
  • E. Suzanne
    Suzanne is a feminine given name of French origin, derived from the Hebrew name Shoshannah meaning “lily.”
  • 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: Sue
Triple: [Bad Santa, mainCharacter, Sue]
Generated description
Sue is a character from the dark comedy film "Bad Santa," known as the love interest of the main antihero, Willie T. Soke.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Sue
Target entity description: Sue is a character from the dark comedy film "Bad Santa," known as the love interest of the main antihero, Willie T. Soke.
  • A. Sue
    Sue is the given name of Sue Storm, the Invisible Woman and a central member of Marvel’s superhero team the Fantastic Four.
  • B. Sue
    Sue is the tough, resilient male protagonist of the humorous country song "A Boy Named Sue," whose life is shaped by the hardships caused by his traditionally feminine name.
  • C. Suzie
    Suzie is a brilliant, tech-savvy girl from Stranger Things who helps Dustin Henderson and his friends by providing crucial scientific and hacking assistance.
  • D. Suzanne
    Suzanne is a central character in Steve Martin’s play "Picasso at the Lapin Agile," representing a young woman entangled romantically with both Picasso and other men in the bohemian Parisian setting.
  • E. Suzanne
    "Suzanne" is a renowned song by Leonard Cohen, celebrated for its poetic lyrics and haunting melody.
  • 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_69d381b3e328819094b23b8edcd29b5a completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e97106448190a075948e63184f47 completed April 7, 2026, 11:24 a.m.
NED1 Entity disambiguation (via context triple) batch_69d79550b2ec8190ada086ddfeb398af completed April 9, 2026, 12:02 p.m.
NEDg Description generation batch_69d7985e7fc081909fd1ba1dc6f7338c completed April 9, 2026, 12:15 p.m.
NED2 Entity disambiguation (via description) batch_69d799917ab881909a947ad8059652c6 completed April 9, 2026, 12:20 p.m.
Created at: April 6, 2026, 12:01 p.m.