Triple

T6305814
Position Surface form Disambiguated ID Type / Status
Subject Grimsby E141371 entity
Predicate hasTwinTown P919 FINISHED
Object Bremerhaven E177141 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: Bremerhaven | Statement: [Grimsby, hasTwinTown, Bremerhaven]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bremerhaven
Context triple: [Grimsby, hasTwinTown, Bremerhaven]
  • A. Bremerhaven chosen
    Bremerhaven is a major German port city on the North Sea, known for its maritime industry, shipbuilding, and role as a key hub for trade and logistics.
  • B. Itzehoe
    Itzehoe is a historic town in northern Germany known for its medieval origins and role as a regional center in the state of Schleswig-Holstein.
  • C. Travemünde
    Travemünde is a Baltic Sea resort town and seaside district of Lübeck in northern Germany, known for its beaches, harbor, and maritime tourism.
  • D. Bremen
    Bremen is a city-state in northwestern Germany comprising the cities of Bremen and Bremerhaven, known for its historic Hanseatic heritage and major port on the Weser River.
  • E. Laboe
    Laboe is a seaside town in northern Germany known for its Baltic Sea beaches and the Laboe Naval Memorial overlooking Kiel Bay.
  • 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_69c008cf0ad4819095def81e2bd42f9f completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c06479acec819090306a155a03b774 completed March 22, 2026, 9:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69c5e44527488190b3d605e917c8dfb2 completed March 27, 2026, 1:58 a.m.
Created at: March 22, 2026, 4:28 p.m.