Triple

T1490902
Position Surface form Disambiguated ID Type / Status
Subject Down and Out in the Magic Kingdom E29575 entity
Predicate mainCharacter P1183 FINISHED
Object Debra
Debra is a central character in Cory Doctorow's science fiction novel "Down and Out in the Magic Kingdom," set in a futuristic, reputation-based society at Disney World.
 E214105 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: Debra | Statement: [Down and Out in the Magic Kingdom, mainCharacter, Debra]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Debra
Context triple: [Down and Out in the Magic Kingdom, mainCharacter, Debra]
  • A. Deanie
    Deanie is a diminutive or affectionate nickname commonly used for someone named Dean.
  • B. Diane
    Diane is a feminine given name of Latin origin, derived from the name of the Roman goddess Diana.
  • C. Deborah Ann Minardos
    Deborah Ann Minardos was an American actress best known as the third wife of Hollywood star Tyrone Power.
  • D. Sandra
    Sandra is the given name of Sandra Day O’Connor, the first woman to serve as a Justice on the United States Supreme Court.
  • E. Marcia
    Marcia was the mother of the Roman emperor Trajan and a member of the provincial Roman aristocracy in Hispania.
  • 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: Debra
Triple: [Down and Out in the Magic Kingdom, mainCharacter, Debra]
Generated description
Debra is a central character in Cory Doctorow's science fiction novel "Down and Out in the Magic Kingdom," set in a futuristic, reputation-based society at Disney World.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Debra
Target entity description: Debra is a central character in Cory Doctorow's science fiction novel "Down and Out in the Magic Kingdom," set in a futuristic, reputation-based society at Disney World.
  • A. Deanie
    Deanie is a diminutive or affectionate nickname commonly used for someone named Dean.
  • B. Diane
    Diane is a feminine given name of Latin origin, derived from the name of the Roman goddess Diana.
  • C. Deborah Ann Minardos
    Deborah Ann Minardos was an American actress best known as the third wife of Hollywood star Tyrone Power.
  • D. Sandra
    Sandra is the given name of Sandra Day O’Connor, the first woman to serve as a Justice on the United States Supreme Court.
  • E. Marcia
    Marcia was the mother of the Roman emperor Trajan and a member of the provincial Roman aristocracy in Hispania.
  • 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_69a498da82e08190ba833330d05f380f completed March 1, 2026, 7:51 p.m.
NER Named-entity recognition batch_69a4c6c3ace4819081bc2b86ee2486b6 completed March 1, 2026, 11:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69adeabea0d88190b0bd83aece8c7b55 completed March 8, 2026, 9:31 p.m.
NEDg Description generation batch_69adeea29fd4819099e1ac22b9ce123f completed March 8, 2026, 9:48 p.m.
NED2 Entity disambiguation (via description) batch_69adef4913608190824764bd79821a7e completed March 8, 2026, 9:51 p.m.
Created at: March 1, 2026, 8:12 p.m.