Triple

T2124469
Position Surface form Disambiguated ID Type / Status
Subject Monsters, Inc. E46395 entity
Predicate hasCharacter P2308 FINISHED
Object Roz
Roz is the gruff, slug-like administrator in Pixar's "Monsters, Inc." who secretly oversees the Child Detection Agency.
 E236489 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: Roz | Statement: [Monsters, Inc., hasCharacter, Roz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Roz
Context triple: [Monsters, Inc., hasCharacter, Roz]
  • A. Roz
    Roz is one of the central protagonists in Margaret Atwood's novel "The Robber Bride," known for her sharp wit, business success, and complex friendship with the other women targeted by the enigmatic Zenia.
  • B. Ró
    Ró is a shortened given name or nickname derived from the name Róbert.
  • C. Robin
    Robin is a given name commonly used in various cultures, often as a diminutive or variant of names like Robert.
  • D. Rae
    Rae is a given name used across various cultures, often as a short form or variant of names like Rachel or Raymond.
  • E. Rolph
    Rolph is a surname most notably associated with James Rolph, a prominent early 20th-century American politician and former mayor of San Francisco and governor of California.
  • 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: Roz
Triple: [Monsters, Inc., hasCharacter, Roz]
Generated description
Roz is the gruff, slug-like administrator in Pixar's "Monsters, Inc." who secretly oversees the Child Detection Agency.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Roz
Target entity description: Roz is the gruff, slug-like administrator in Pixar's "Monsters, Inc." who secretly oversees the Child Detection Agency.
  • A. Roz
    Roz is one of the central protagonists in Margaret Atwood's novel "The Robber Bride," known for her sharp wit, business success, and complex friendship with the other women targeted by the enigmatic Zenia.
  • B. Ró
    Ró is a shortened given name or nickname derived from the name Róbert.
  • C. Robin
    Robin is a given name commonly used in various cultures, often as a diminutive or variant of names like Robert.
  • D. Rae
    Rae is a given name used across various cultures, often as a short form or variant of names like Rachel or Raymond.
  • E. Rolph
    Rolph is a surname most notably associated with James Rolph, a prominent early 20th-century American politician and former mayor of San Francisco and governor of California.
  • 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_69a88a1626548190ae59a5028c3baa8e completed March 4, 2026, 7:37 p.m.
NER Named-entity recognition batch_69abbb55cb2c8190aab8199da3335032 completed March 7, 2026, 5:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae519bfdb08190a7b715fbc5fd3f41 completed March 9, 2026, 4:50 a.m.
NEDg Description generation batch_69ae521c7810819086b88bb5f062597e completed March 9, 2026, 4:52 a.m.
NED2 Entity disambiguation (via description) batch_69ae52e79c788190bbe6eb5baba08a71 completed March 9, 2026, 4:56 a.m.
Created at: March 4, 2026, 7:44 p.m.