Triple

T1695029
Position Surface form Disambiguated ID Type / Status
Subject Krefeld E36636 entity
Predicate twinTown P1072 FINISHED
Object Dünkirchen E182674 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: Dünkirchen | Statement: [Krefeld, twinTown, Dünkirchen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dünkirchen
Context triple: [Krefeld, twinTown, Dünkirchen]
  • A. Duinkerke chosen
    Duinkerke is the Dutch name for Dunkirk, a historic port city in northern France known for its pivotal World War II evacuation.
  • B. Warburg
    Warburg is a prominent German-Jewish banking and philanthropic family historically influential in international finance and economic policy.
  • C. Dieppe
    Dieppe is a historic port city and seaside resort on the English Channel in northern France, known for its pebbled beaches, cliffs, and role in maritime trade and warfare.
  • D. Bremerhaven
    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.
  • E. Arnhem
    Arnhem is a city in the eastern Netherlands best known as the site of a major World War II battle during Operation Market Garden.
  • 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_69a886163dec8190859c514232a37a05 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa62b3b8908190afc3f9e4a384684f completed March 6, 2026, 5:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad8ac9ed2c81909fe3fe40515526de completed March 8, 2026, 2:42 p.m.
Created at: March 4, 2026, 7:30 p.m.