Triple

T2045096
Position Surface form Disambiguated ID Type / Status
Subject Lower Bavaria E45432 entity
Predicate seatOfGovernment P761 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: [Lower Bavaria, seatOfGovernment, Landshut]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Landshut
Context triple: [Lower Bavaria, seatOfGovernment, 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. Rosenheim
    Rosenheim is a town in Upper Bavaria, Germany, known as a regional economic and transportation hub near the Alps.
  • E. Passau
    Passau is a historic city in southeastern Germany, renowned for its picturesque old town and location at the meeting point of three rivers: the Danube, Inn, and Ilz.
  • 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_69a8891948208190ab7898da21824c77 completed March 4, 2026, 7:33 p.m.
NER Named-entity recognition batch_69abb9728f688190939d7c4df524f9b4 completed March 7, 2026, 5:36 a.m.
NED1 Entity disambiguation (via context triple) batch_69bd6f6fe04c8190bffabb9225ef6c2a completed March 20, 2026, 4:01 p.m.
Created at: March 4, 2026, 7:39 p.m.