Triple

T16070139
Position Surface form Disambiguated ID Type / Status
Subject A Boogie wit da Hoodie E389838 entity
Predicate basedIn P40 FINISHED
Object The Bronx E8102 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: The Bronx | Statement: [A Boogie wit da Hoodie, basedIn, The Bronx]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: The Bronx
Context triple: [A Boogie wit da Hoodie, basedIn, The Bronx]
  • A. The Bronx chosen
    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. 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.
  • C. Brooklyn
    Brooklyn is a small inner-ring suburb of Cleveland located in Cuyahoga County, Ohio.
  • D. Brooklyn
    Brooklyn is a residential suburb within the Milnerton area of Cape Town, South Africa.
  • E. 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.
  • 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_69d86daf32ec8190a8c0466c8f49c3c0 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e183bd9578819097e7cb1108b1f6f7 completed April 17, 2026, 12:50 a.m.
NED1 Entity disambiguation (via context triple) batch_69fffee94e1c8190ae81e2d5be082982 completed May 10, 2026, 3:43 a.m.
Created at: April 10, 2026, 4:57 a.m.