Triple

T2071933
Position Surface form Disambiguated ID Type / Status
Subject Williamsburg E44832 entity
Predicate hasViewOf P854 FINISHED
Object Manhattan 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: Manhattan | Statement: [Williamsburg, hasViewOf, Manhattan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Manhattan
Context triple: [Williamsburg, hasViewOf, Manhattan]
  • A. 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.
  • B. New York City
    New York City is the largest city in the United States, a global center of finance, culture, media, and technology.
  • 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. Brooklyn
    Brooklyn is a small inner-ring suburb of Cleveland located in Cuyahoga County, Ohio.
  • E. 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.
  • 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_69a88916c2b48190a5ca2e9b12cad3ed completed March 4, 2026, 7:33 p.m.
NER Named-entity recognition batch_69abba0d20bc8190b19a32157f8b1607 completed March 7, 2026, 5:39 a.m.
NED1 Entity disambiguation (via context triple) batch_69b28d474f10819090cef63f1b93646a completed March 12, 2026, 9:54 a.m.
Created at: March 4, 2026, 7:41 p.m.