Triple

T14984113
Position Surface form Disambiguated ID Type / Status
Subject FDNY Ladder Company 110 E373656 entity
Predicate serviceArea P82 FINISHED
Object Brooklyn 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 | Statement: [FDNY Ladder Company 110, serviceArea, Brooklyn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Brooklyn
Context triple: [FDNY Ladder Company 110, serviceArea, Brooklyn]
  • 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 2015 period drama film about a young Irish woman who emigrates to New York in the 1950s and must choose between her new life in America and her roots in Ireland.
  • D. Brooklyn
    Brooklyn is a residential suburb within the Milnerton area of Cape Town, South Africa.
  • E. Brooklyn
    Brooklyn is a small city in Poweshiek County, Iowa, known for its collection of flags from around the world and its nickname "Community of Flags."
  • 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_69d85ccc84388190aa151e5173370c8d completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded6ff4a7c8190ab7554f3a1a09b67 completed April 15, 2026, 12:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69feae048fa08190ba5719ca9868b50d completed May 9, 2026, 3:46 a.m.
Created at: April 10, 2026, 2:52 a.m.