Triple

T386351
Position Surface form Disambiguated ID Type / Status
Subject Manhattan E8787 entity
Predicate contains P35 FINISHED
Object Harlem E8787 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: Harlem | Statement: [Manhattan, contains, Harlem]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Harlem
Context triple: [Manhattan, contains, Harlem]
  • A. The Bronx
    The Bronx is one of the five boroughs of New York City, known as the birthplace of hip-hop and home to Yankee Stadium and the Bronx Zoo.
  • B. Manhattan chosen
    Manhattan is the densely populated, iconic core borough of New York City, known for its skyscrapers, cultural institutions, and role as a global financial and media center.
  • C. Brooklyn
    Brooklyn is a populous and culturally diverse borough of New York City known for its distinct neighborhoods, arts scene, and iconic landmarks like the Brooklyn Bridge.
  • D. Bedford–Stuyvesant
    Bedford–Stuyvesant is a historically significant Brooklyn neighborhood known for its rich African-American cultural heritage, brownstone architecture, and vibrant community life.
  • E. Queens
    Queens is one of the five boroughs of New York City, known for its ethnic diversity, major airports, and mix of residential neighborhoods and commercial centers.
  • 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_69a2e7f47dd08190a4e294ccbbe46cd4 completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2ec447b5481908a5a084787b44ced completed Feb. 28, 2026, 1:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69a40ad425a881909eea63c64a683c0f completed March 1, 2026, 9:45 a.m.
Created at: Feb. 28, 2026, 1:08 p.m.