Triple

T15687389
Position Surface form Disambiguated ID Type / Status
Subject OHV E380236 entity
Predicate administrativeState P23251 FINISHED
Object Land Brandenburg E46660 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: Land Brandenburg | Statement: [OHV, administrativeState, Land Brandenburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Land Brandenburg
Context triple: [OHV, administrativeState, Land Brandenburg]
  • A. Weimarer Land
    Weimarer Land is a rural district in the German state of Thuringia, known for its historic towns, cultural heritage, and agricultural landscapes surrounding the city of Weimar.
  • B. Mecklenburgische Seenplatte district
    The Mecklenburgische Seenplatte district is a large rural district in the German state of Mecklenburg-Vorpommern, renowned for its extensive lake district and natural landscapes.
  • C. Brandenburg chosen
    Brandenburg is a federal state in northeastern Germany that surrounds Berlin and is known for its lakes, forests, and historic Prussian heritage.
  • D. Brandenburg
    Brandenburg is a small city in Meade County, Kentucky, situated along the Ohio River and serving as the county seat.
  • E. State of Bremen
    The State of Bremen is a small federal state in northwestern Germany comprising the cities of Bremen and Bremerhaven, known for its historic Hanseatic heritage and major port facilities.
  • 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_69d86d99e860819094b6957cde470f2c completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e04f4cee5481908699fbb2b7bdd2f6 completed April 16, 2026, 2:54 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff6ee91340819086c8f51e8eb477aa completed May 9, 2026, 5:29 p.m.
Created at: April 10, 2026, 4:44 a.m.