Triple

T8640071
Position Surface form Disambiguated ID Type / Status
Subject Hollywoodland E204622 entity
Predicate producer P490 FINISHED
Object Glenn Williamson E251895 NE FINISHED

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: Glenn Williamson | Statement: [Hollywoodland, producer, Glenn Williamson]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Glenn Williamson
Context triple: [Hollywoodland, producer, Glenn Williamson]
  • A. Glenn Williamson chosen
    Glenn Williamson is a film producer known for his work on independent and character-driven movies, including the dark comedy-drama "Sunshine Cleaning."
  • B. Glen Williams
    Glen Williams is a small historic village community located within the town of Halton Hills in Ontario, Canada.
  • C. Glenn Roberts
    Glenn Roberts is an American grain expert and founder of Anson Mills, renowned for reviving heirloom Southern grains and rice varieties, including Carolina Gold rice.
  • D. Glenn Padnick
    Glenn Padnick is an American television and film producer best known as a co-founder of Castle Rock Entertainment and an early executive behind hit series like Seinfeld.
  • E. Glen Stanly
    Glen Stanly is a fictional character in Herman Melville’s novel "Pierre; or, The Ambiguities," involved in the complex social and psychological dynamics surrounding the protagonist.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69ca834ca1c88190a11ffb0200342fac completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc47650a14819094855aa8d062ebbc completed March 31, 2026, 10:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf88b20fec819086a1f1f3554c90e4 completed April 3, 2026, 9:30 a.m.
Created at: March 30, 2026, 6:28 p.m.