Triple

T19460850
Position Surface form Disambiguated ID Type / Status
Subject Daniel Gerson E486863 entity
Predicate notableWork P4 FINISHED
Object Monsters University NE NERFINISHED

How this triple was built (2 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: Monsters University | Statement: [Daniel Gerson, notableWork, Monsters University]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Monsters University
Context triple: [Daniel Gerson, notableWork, Monsters University]
  • A. Monsters University chosen
    Monsters University is a 2013 Pixar animated prequel to Monsters, Inc. that follows Mike and Sulley’s college years as they train to become professional scarers.
  • B. Monstropolis
    Monstropolis is the bustling, monster-populated city that serves as the primary setting of Pixar’s "Monsters, Inc." franchise.
  • C. Monsters, Inc.
    Monsters, Inc. is a 2001 animated comedy film that follows two monsters working at a scream-powered energy company whose lives are upended when a human child enters their world.
  • D. Monstars
    The Monstars are the villainous alien basketball team that serves as the primary antagonists in the animated–live action film "Space Jam."
  • E. Monsters at Work
    Monsters at Work is an animated television series set in the Monsters, Inc. universe that follows new recruits navigating the transition from scaring to laugh power at the iconic monster factory.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e8d86d608190bd199a98d0297f27 completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e633c983f481908b2684dc4380b889 completed April 20, 2026, 2:10 p.m.
Created at: April 10, 2026, 1:38 p.m.