Triple

T9194497
Position Surface form Disambiguated ID Type / Status
Subject Tony Buddenbrook E220668 entity
Predicate associatedWithPlace P2830 FINISHED
Object Lübeck E56916 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: Lübeck | Statement: [Tony Buddenbrook, associatedWithPlace, Lübeck]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lübeck
Context triple: [Tony Buddenbrook, associatedWithPlace, Lübeck]
  • A. Lübeck chosen
    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.
  • 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. Rostock
    Rostock is a historic Hanseatic city in northern Germany known for its significant seaport on the Baltic Sea and its long maritime and trading tradition.
  • D. Flensburg
    Flensburg is a historic port city in northern Germany near the Danish border, known for its maritime heritage and role as a regional administrative and cultural center in Schleswig-Holstein.
  • E. Wismar
    Wismar is a historic Hanseatic port city on Germany’s Baltic Sea coast, known for its well-preserved medieval architecture and UNESCO-listed old town.
  • 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_69ca83e7ba70819088b74866d9da2c30 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69ccd5c3614c81909e26417e00fdfa11 completed April 1, 2026, 8:22 a.m.
NED1 Entity disambiguation (via context triple) batch_69d1077a9cb0819086996b4930a44a93 completed April 4, 2026, 12:43 p.m.
Created at: March 30, 2026, 7:25 p.m.