Triple

T5855108
Position Surface form Disambiguated ID Type / Status
Subject Michael Van Valkenburgh Associates E130131 entity
Predicate headquartersLocation P62 FINISHED
Object Brooklyn, New York E5446 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: Brooklyn, New York | Statement: [Michael Van Valkenburgh Associates, headquartersLocation, Brooklyn, New York]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Brooklyn, New York
Context triple: [Michael Van Valkenburgh Associates, headquartersLocation, Brooklyn, New York]
  • A. Brooklyn chosen
    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.
  • B. Brooklyn
    Brooklyn is a small inner-ring suburb of Cleveland located in Cuyahoga County, Ohio.
  • C. Brooklyn
    Brooklyn is a residential suburb within the Milnerton area of Cape Town, South Africa.
  • D. Brooklyn
    Brooklyn is a historic, primarily residential neighborhood in inner southeast Portland, Oregon, known for its close-in location, community feel, and mix of older homes and light industrial areas.
  • E. Williamsburg, Brooklyn
    Williamsburg, Brooklyn is a vibrant neighborhood in New York City known for its arts scene, trendy restaurants and bars, and a large population of young professionals and creatives.
  • 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_69c0084de39081909eb34e6bed74215a completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c03554651c8190b3009d41eecf6779 completed March 22, 2026, 6:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69c13540fa788190a09a509267bdb147 completed March 23, 2026, 12:42 p.m.
Created at: March 22, 2026, 3:55 p.m.