Triple

T19444406
Position Surface form Disambiguated ID Type / Status
Subject Pier 57 E486433 entity
Predicate near P350 FINISHED
Object Meatpacking District 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: Meatpacking District | Statement: [Pier 57, near, Meatpacking District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Meatpacking District
Context triple: [Pier 57, near, Meatpacking District]
  • A. Meatpacking District chosen
    The Meatpacking District is a trendy Manhattan neighborhood known for its cobblestone streets, high-end boutiques, nightlife, and the southern end of the High Line park.
  • B. Flatiron District
    The Flatiron District is a Manhattan neighborhood known for its iconic Flatiron Building, historic architecture, and role as a hub for tech companies and trendy dining.
  • C. Nolita
    Nolita is a trendy, upscale neighborhood in Lower Manhattan known for its boutique shopping, stylish restaurants, and historic, narrow streets.
  • D. Greenwich Village
    Greenwich Village is a historic, bohemian neighborhood in Lower Manhattan, New York City, long associated with artists, writers, and countercultural movements.
  • E. Leather District
    The Leather District is a small historic neighborhood in Boston known for its 19th-century brick warehouse buildings and former leather industry.
  • 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_69d8e8d7ad488190a3373045029b0f3b completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e63387e2048190bfb13fea434ddb46 completed April 20, 2026, 2:09 p.m.
Created at: April 10, 2026, 1:38 p.m.