Triple

T1413665
Position Surface form Disambiguated ID Type / Status
Subject Brunswick station E31861 entity
Predicate city P40 FINISHED
Object Brunswick E148165 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: Brunswick | Statement: [Brunswick station, city, Brunswick]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Brunswick
Context triple: [Brunswick station, city, Brunswick]
  • A. Brunswick
    Brunswick is a historic city in northern Germany known for its medieval heritage and as the birthplace of mathematician Carl Friedrich Gauss.
  • B. Brunswick chosen
    Brunswick is a coastal town in Maine known for its historic charm, cultural amenities, and role as the home of Bowdoin College.
  • C. Lunenburg
    Lunenburg is a small town in north-central Massachusetts known for its residential character and proximity to commuter rail service into the Boston area.
  • D. Lunenburg
    Lunenburg is a historic coastal town in eastern Canada renowned for its colorful waterfront, shipbuilding heritage, and UNESCO World Heritage–listed Old Town.
  • E. Hampton
    Hampton is a suburban town in the London Borough of Richmond upon Thames, England, situated on the north bank of the River Thames.
  • 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_69a49919a994819086528951bc224775 completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c3e476f08190aed1576805c62462 completed March 1, 2026, 10:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad1c97ba748190a227457bcb87a733 completed March 8, 2026, 6:52 a.m.
Created at: March 1, 2026, 7:59 p.m.