Triple

T6620189
Position Surface form Disambiguated ID Type / Status
Subject Pregel River E149653 entity
Predicate flowsThrough P225 FINISHED
Object Königsberg E19236 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: Königsberg | Statement: [Pregel River, flowsThrough, Königsberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Königsberg
Context triple: [Pregel River, flowsThrough, Königsberg]
  • A. Königsberg chosen
    Königsberg was a historic Prussian city on the Baltic Sea, renowned as a major cultural and intellectual center of East Prussia and later known as Kaliningrad.
  • B. Elbing
    Elbing is a historic Baltic port city, now known as Elbląg in Poland, that played a notable role in medieval trade as part of the Hanseatic commercial network.
  • C. Potsdam
    Potsdam is a historic German city near Berlin, known for its palaces, parks, and role in major 20th-century diplomatic events.
  • D. Ribnitz-Damgarten
    Ribnitz-Damgarten is a small town in northeastern Germany known as the “Bernsteinstadt” (Amber Town) for its long tradition of amber processing and its location near the Baltic Sea.
  • E. Torgau
    Torgau is a historic town in eastern Germany, known for its Renaissance architecture and its role as a key meeting point of Allied forces near the end of World War II.
  • 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_69c687ed8a9c81908bb671717cb192ef completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6af7aff44819089da6145e1ef5f76 completed March 27, 2026, 4:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6eee8740881908b4fafb12db6b7f3 completed March 27, 2026, 8:56 p.m.
Created at: March 27, 2026, 1:58 p.m.