Triple

T35728108
Position Surface form Disambiguated ID Type / Status
Subject Tokyo! E1032670 entity
Predicate screenwriterOfSegmentInteriorDesign P169297 FINISHED
Object Michel Gondry 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: Michel Gondry | Statement: [Tokyo!, screenwriterOfSegmentInteriorDesign, Michel Gondry]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: screenwriterOfSegmentInteriorDesign
Context triple: [Tokyo!, screenwriterOfSegmentInteriorDesign, Michel Gondry]
  • A. screenwriterDepictionBy
    Indicates a relationship where a screenwriter is portrayed or represented by another entity, such as in a work, record, or description.
  • B. screenwriterInvolved chosen
    Indicates that a screenwriter participated in the creation or development of a particular work or project.
  • C. screenwriterInstanceOf
    Indicates that a screenwriter belongs to or is classified as a specific type, category, or class of entity.
  • D. screenwriterForStudio
    Indicates that a person serves as a screenwriter employed by or writing for a particular studio.
  • E. screenwriterInterpretationBy
    Indicates that a particular interpretation or version of a work is created or provided by a specific screenwriter.
  • F. None of above.

Provenance (3 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_69f76e102b5881909e5d63a30a5cecbe completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7b0e5744c8190a22c1e1d6fcfa466 completed May 3, 2026, 8:32 p.m.
PD Predicate disambiguation batch_69f7ab70d034819080295628497d8582 completed May 3, 2026, 8:09 p.m.
Created at: May 3, 2026, 4:05 p.m.