Triple

T8862534
Position Surface form Disambiguated ID Type / Status
Subject Wettin-Löbejün E210926 entity
Predicate formedByMergerOf P77 FINISHED
Object Beidersee E819504 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: Beidersee | Statement: [Wettin-Löbejün, formedByMergerOf, Beidersee]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Beidersee
Context triple: [Wettin-Löbejün, formedByMergerOf, Beidersee]
  • A. Beidersee chosen
    Beidersee is a village in the Saalekreis district of Saxony-Anhalt, Germany, that forms part of the town of Wettin-Löbejün.
  • B. Pfäffikersee
    Pfäffikersee is a small lake in the Swiss canton of Zürich known for its scenic surroundings, nature reserves, and recreational opportunities such as hiking and birdwatching.
  • C. Stölpchensee
    Stölpchensee is a small lake in southwestern Berlin, Germany, known for its scenic setting within the Grunewald forest and its connection to the nearby Großer Wannsee.
  • D. Rothsee
    Rothsee is an artificial recreational lake in Middle Franconia, Bavaria, popular for swimming, sailing, and other water sports.
  • E. Ziegelsee
    Ziegelsee is a lake in the city of Schwerin in northern Germany, known for its scenic waterfront and role in the region’s interconnected lake system.
  • 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_69ca838bbddc8190ab546d737e5d350f completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc610263048190931bb2c3ac573a08 completed April 1, 2026, 12:04 a.m.
NED1 Entity disambiguation (via context triple) batch_69d1c3ed827c8190899cb2ae9561765e completed April 5, 2026, 2:07 a.m.
Created at: March 30, 2026, 6:50 p.m.