Triple

T1558214
Position Surface form Disambiguated ID Type / Status
Subject Weser E33257 entity
Predicate passesThroughCity P416 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: [Weser, passesThroughCity, Bremerhaven]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bremerhaven
Context triple: [Weser, passesThroughCity, 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. 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.
  • C. Lübeck
    Lübeck is a historic Hanseatic city in northern Germany renowned for its medieval architecture and long-standing role as a key trading hub on the Baltic Sea.
  • D. Delmenhorst
    Delmenhorst is a mid-sized industrial and commuter city in northwestern Germany, located near Bremen in the federal state of Lower Saxony.
  • E. Hamburg
    Hamburg is Germany’s second-largest city and a major northern European port and cultural center on the River Elbe.
  • 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_69a885ef9cf48190b0af0f5ce3d02231 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a9088355048190adad5ea2bb558d13 completed March 5, 2026, 4:37 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad401e12088190b6f0f5b0d8a423cf completed March 8, 2026, 9:23 a.m.
Created at: March 4, 2026, 7:27 p.m.