Triple

T13433923
Position Surface form Disambiguated ID Type / Status
Subject Bayerisch Eisenstein E320180 entity
Predicate locatedIn P40 FINISHED
Object Lower Bavaria E45432 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: Lower Bavaria | Statement: [Bayerisch Eisenstein, locatedIn, Lower Bavaria]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lower Bavaria
Context triple: [Bayerisch Eisenstein, locatedIn, Lower Bavaria]
  • A. Lower Bavaria chosen
    Lower Bavaria is an administrative region in southeastern Germany known for its rural landscapes, historic towns, and location along the Danube River.
  • B. Upper Bavaria
    Upper Bavaria is a southeastern administrative region of Germany known for including the city of Munich, the Bavarian Alps, and many of the state’s most famous cultural and natural landmarks.
  • C. Oberpfalz
    Oberpfalz is a region in eastern Bavaria, Germany, known for its distinct cultural traditions, historical towns, and rich intangible heritage.
  • D. Upper Franconia
    Upper Franconia is a region in northern Bavaria, Germany, known for its historic towns, dense concentration of breweries, and rich Franconian cultural heritage.
  • E. Mittelfranken
    Mittelfranken is a region in the German state of Bavaria known for its rich cultural traditions, historic cities, and significant contributions to the state's intangible cultural heritage.
  • 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_69d80761e6cc8190a90c844589998ecc completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbaee29fec81908b07b4fca2922242 completed April 12, 2026, 2:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7398da07081908c3eca6fc4213930 completed May 3, 2026, 12:03 p.m.
Created at: April 9, 2026, 9:40 p.m.