Triple

T14933902
Position Surface form Disambiguated ID Type / Status
Subject Braniewo E372339 entity
Predicate formerName P65 FINISHED
Object Braunsberg E511202 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: Braunsberg | Statement: [Braniewo, formerName, Braunsberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Braunsberg
Context triple: [Braniewo, formerName, Braunsberg]
  • A. Braunsberg chosen
    Braunsberg is a locality in former East Prussia (now in Poland) known for its proximity to the World War II Heiligenbeil pocket battlefield.
  • B. Bergneustadt
    Bergneustadt is a small town in North Rhine-Westphalia, Germany, known for its location in the hilly Oberbergischer Kreis region and its traditional half-timbered architecture.
  • C. Osterburg
    Osterburg is a small town in the German state of Saxony-Anhalt, known for its historic architecture and rural surroundings.
  • D. Oberhaus
    The Oberhaus is the modern upper chamber of a bicameral legislature, functioning as the contemporary equivalent of the historical Erste Kammer.
  • E. Burgstädt
    Burgstädt is a small town in the German state of Saxony, known for its traditional architecture and location near the city of Chemnitz.
  • 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_69d85cc9da0c81908d583ca3f63a3908 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded646a0808190ba5c0c91bde011c5 completed April 15, 2026, 12:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69fec8741c048190b549782f49969f6a completed May 9, 2026, 5:39 a.m.
Created at: April 10, 2026, 2:37 a.m.