Triple

T13063468
Position Surface form Disambiguated ID Type / Status
Subject Duchy of Bavaria E329255 entity
Predicate capital P234 FINISHED
Object Burghausen E621310 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: Burghausen | Statement: [Duchy of Bavaria, capital, Burghausen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Burghausen
Context triple: [Duchy of Bavaria, capital, Burghausen]
  • A. Burghausen chosen
    Burghausen is a historic Bavarian town in southeastern Germany, renowned for its remarkably well-preserved medieval old town and one of the longest castle complexes in the world.
  • B. Haßfurt
    Haßfurt is a small town in northern Bavaria, Germany, situated on the Main River and known for its historic architecture and regional administrative role.
  • C. Traunstein
    Traunstein is a town in southeastern Bavaria, Germany, known as a regional administrative and cultural center near the Chiemsee and the Alps.
  • D. Forchheim
    Forchheim is a town in Upper Franconia, Bavaria, Germany, known for its historic old town and location along major regional rail and road routes.
  • E. Wolfratshausen
    Wolfratshausen is a Bavarian town in southern Germany known for its historic old town, riverside setting on the Loisach and Isar, and proximity to Munich and the Alps.
  • 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_69d80771749c81909a6d9197b9504872 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d980e9bdfc81908eb90fb50597df64 completed April 10, 2026, 10:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69fde158a5a48190b3945945f94f97a0 completed May 8, 2026, 1:12 p.m.
Created at: April 9, 2026, 8:59 p.m.