Triple

T354076
Position Surface form Disambiguated ID Type / Status
Subject New York metropolitan area E7505 entity
Predicate containsCity P294 FINISHED
Object Paterson E19335 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: Paterson | Statement: [New York metropolitan area, containsCity, Paterson]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Paterson
Context triple: [New York metropolitan area, containsCity, Paterson]
  • A. Paterson, New Jersey chosen
    Paterson, New Jersey is a historic industrial city in northern New Jersey known for its diverse immigrant communities, including a significant Dutch American presence.
  • B. Newark
    Newark is a major city in northern New Jersey known for its historic significance, diverse communities, and role as a cultural and transportation hub in the New York metropolitan area.
  • C. Camden
    Camden is a vibrant inner borough of London known for its alternative culture, markets, live music venues, and canalside atmosphere.
  • D. Camden
    Camden is a city in New Jersey located directly across the Delaware River from Philadelphia, known historically as an industrial hub and for its proximity to the larger Philadelphia metropolitan area.
  • E. Montclair
    Montclair is a residential, hillside neighborhood in Oakland, California, known for its wooded canyons, winding streets, and small village-style commercial district.
  • 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_69a2e7e696948190bebc966535995e45 completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2eb8312f4819084dc222e665fded3 completed Feb. 28, 2026, 1:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69a4efc821b48190af6d3cd88ab3f980 completed March 2, 2026, 2:02 a.m.
Created at: Feb. 28, 2026, 1:08 p.m.