Triple

T20699987
Position Surface form Disambiguated ID Type / Status
Subject Confessions of a Window Cleaner E508752 entity
Predicate leadRoleName P12885 FINISHED
Object Timothy Lea 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: Timothy Lea | Statement: [Confessions of a Window Cleaner, leadRoleName, Timothy Lea]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Timothy Lea
Context triple: [Confessions of a Window Cleaner, leadRoleName, Timothy Lea]
  • A. Timothy Lea chosen
    Timothy Lea is the bumbling, womanizing protagonist of the British sex-comedy "Confessions" series, best known for his misadventures as a window cleaner.
  • B. Timothy Hamilton
    Timothy Hamilton is the brother of professional surfer and shark attack survivor Bethany Hamilton.
  • C. Timothy Arthur
    Timothy Arthur, often known as T. S. Arthur, was a 19th-century American author and temperance advocate best known for his moralistic tales such as "Ten Nights in a Bar-Room and What I Saw There."
  • D. Timothy Hunter
    Timothy Hunter is a bespectacled British teenager in DC/Vertigo comics who discovers he may become the world’s greatest magician and must choose how to use his immense magical potential.
  • E. Timothy Matthews
    Timothy Matthews is a personal name shared by multiple individuals, including professionals in fields such as sports, media, and public service.
  • 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_69e0b4c2b2a481909e31e9cb8f81ab55 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6c18a77308190b7c2517d82a145cd completed April 21, 2026, 12:15 a.m.
Created at: April 16, 2026, 12:12 p.m.