Triple

T13063465
Position Surface form Disambiguated ID Type / Status
Subject Duchy of Bavaria E329255 entity
Predicate capital P234 FINISHED
Object Landshut E302865 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: Landshut | Statement: [Duchy of Bavaria, capital, Landshut]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Landshut
Context triple: [Duchy of Bavaria, capital, Landshut]
  • A. Landshut chosen
    Landshut is a historic Bavarian city in southeastern Germany known for its well-preserved medieval architecture and the landmark Trausnitz Castle.
  • B. Augsburg
    Augsburg is one of Germany’s oldest cities, a historic Bavarian center known for its rich Renaissance heritage and role as a major medieval trading hub.
  • C. Kempten
    Kempten is a historic town in Bavaria, Germany, considered one of the country’s oldest urban settlements and known for its location in the Allgäu region.
  • D. Kaufbeuren
    Kaufbeuren is a historic Bavarian town in southern Germany known for its well-preserved medieval old town and traditional Swabian culture.
  • E. Altdorf (Landshut)
    Altdorf (Landshut) is a municipality in Lower Bavaria, Germany, situated near the city of Landshut.
  • 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_69fbc311b1248190b9ceb2854e93171a completed May 6, 2026, 10:39 p.m.
Created at: April 9, 2026, 8:59 p.m.