Triple

T9568069
Position Surface form Disambiguated ID Type / Status
Subject The Incredible Mr. Limpet E230837 entity
Predicate narrativeLocation P40 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: [The Incredible Mr. Limpet, narrativeLocation, Brooklyn, New York]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Brooklyn, New York
Context triple: [The Incredible Mr. Limpet, narrativeLocation, 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 small city in Poweshiek County, Iowa, known for its collection of flags from around the world and its nickname "Community of Flags."
  • 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_69ca847f22188190a56e4a97625bef22 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9987cb0c8190af32a1193de54890 completed April 1, 2026, 10:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69d19f5997a48190b8a08c7aee12c90d completed April 4, 2026, 11:31 p.m.
Created at: March 30, 2026, 8:04 p.m.