Triple

T12532518
Position Surface form Disambiguated ID Type / Status
Subject Prince Street station E299603 entity
Predicate servedArea P82 FINISHED
Object SoHo commercial district E54021 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: SoHo commercial district | Statement: [Prince Street station, servedArea, SoHo commercial district]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: SoHo commercial district
Context triple: [Prince Street station, servedArea, SoHo commercial district]
  • A. SoHo
    SoHo is a vibrant commercial and entertainment district in Hong Kong known for its trendy restaurants, bars, and nightlife.
  • B. SoHo chosen
    SoHo is a fashionable Lower Manhattan neighborhood known for its cast-iron architecture, art galleries, and upscale boutiques.
  • C. Garment District
    The Garment District is a New York City neighborhood renowned as the historic center of the American fashion and apparel industry, filled with showrooms, production facilities, and fashion-related businesses.
  • D. SoHo Square
    SoHo Square is a mixed-use commercial and retail center serving as a key shopping and dining destination in Homewood, Alabama.
  • 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 (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_69d6ada5cdd48190860d9ce30aff69be completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d9546b8fd48190ae90e80785b2e2d1 completed April 10, 2026, 7:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6c0d6947c819080d33199d331724c completed May 3, 2026, 3:28 a.m.
Created at: April 8, 2026, 9:57 p.m.