Triple

T17220030
Position Surface form Disambiguated ID Type / Status
Subject Dayton E417952 entity
Predicate hasRelatedName P3889 FINISHED
Object Peyton E132632 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: Peyton | Statement: [Dayton, hasRelatedName, Peyton]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Peyton
Context triple: [Dayton, hasRelatedName, Peyton]
  • A. Peyton chosen
    Peyton is a given name most famously borne by Peyton Randolph, the first president of the Continental Congress in early American history.
  • B. Peyton Flanders
    Peyton Flanders is the manipulative and vengeful nanny who infiltrates a suburban family in the psychological thriller film "The Hand That Rocks the Cradle."
  • C. Peyton Page
    Peyton Page is a relatively uncommon personal name that may refer to various individuals rather than a single widely recognized public figure.
  • D. Peyton Van Den Broeck
    Peyton Van Den Broeck is known as the spouse of Dutch Van Den Broeck, a central character in the crime novel and film "Random Hearts."
  • E. Peyton Westlake
    Peyton Westlake is a disfigured scientist-turned-vigilante who uses synthetic skin and brutal methods to seek revenge in the Darkman film series.
  • 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_69d886d779488190b131369541c04e7d completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e42ddd52d4819098b51d55e063c8ab completed April 19, 2026, 1:20 a.m.
NED1 Entity disambiguation (via context triple) batch_6a01675553b88190a04987b0de62cb15 completed May 11, 2026, 5:21 a.m.
Created at: April 10, 2026, 5:38 a.m.