Triple

T9553544
Position Surface form Disambiguated ID Type / Status
Subject Eastern Bavaria E230483 entity
Predicate contains P35 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: [Eastern Bavaria, contains, Landshut]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Landshut
Context triple: [Eastern Bavaria, contains, 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_69ca847d3be8819099c9dad2a7e786f1 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd99217de48190b528e14fd02ee987 completed April 1, 2026, 10:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69de21a949508190ad16b061ead5ed24 completed April 14, 2026, 11:14 a.m.
Created at: March 30, 2026, 8:02 p.m.