Triple

T17831612
Position Surface form Disambiguated ID Type / Status
Subject Dämeritzsee E445269 entity
Predicate connectsWith P37 FINISHED
Object Seddinsee NE NERFINISHED

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: Seddinsee | Statement: [Dämeritzsee, connectsWith, Seddinsee]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Seddinsee
Context triple: [Dämeritzsee, connectsWith, Seddinsee]
  • A. Seddinsee chosen
    Seddinsee is a lake in southeastern Berlin, Germany, known for its recreational boating, natural shoreline, and role as part of the city’s interconnected waterway network.
  • B. Seevetal
    Seevetal is a large municipality in Lower Saxony, Germany, located just south of Hamburg and known for its suburban character and good transport connections.
  • C. Schwansee
    Schwansee is a picturesque alpine lake in Bavaria, Germany, known for its scenic setting near Neuschwanstein and Hohenschwangau castles.
  • D. Eging am See
    Eging am See is a small Bavarian town in southeastern Germany known for its scenic lakeside setting and proximity to the Bavarian Forest.
  • E. Biggesee
    Biggesee is a large artificial reservoir and popular recreational lake in Germany’s Sauerland region, known for water sports, camping, and scenic hiking areas.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b9f1a6d881909f024bc603111cdb completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e48d248ecc8190b3f0d001b539d960 completed April 19, 2026, 8:07 a.m.
Created at: April 10, 2026, 10:15 a.m.