Triple

T10441224
Position Surface form Disambiguated ID Type / Status
Subject Plön E246173 entity
Predicate hasBodyOfWater P1778 FINISHED
Object Großer Plöner See E875784 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: Großer Plöner See | Statement: [Plön, hasBodyOfWater, Großer Plöner See]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Großer Plöner See
Context triple: [Plön, hasBodyOfWater, Großer Plöner See]
  • A. Großer Plöner See chosen
    Großer Plöner See is one of the largest and most scenic lakes in Schleswig-Holstein, northern Germany, known for its clear waters, islands, and surrounding natural landscapes.
  • B. Schweriner See
    Schweriner See is a large lake in northern Germany that surrounds and characterizes the city of Schwerin, known for its scenic shores and historic lakeside castle.
  • C. Schlachtensee
    Schlachtensee is a lake and popular recreational area in southwestern Berlin, known for swimming, walking trails, and its surrounding forested landscape.
  • D. Malchower See
    Malchower See is a lake in the Malchow area of Berlin, Germany, known for its natural surroundings and local recreational use.
  • E. Ostorfer See
    Ostorfer See is a lake in the German state of Mecklenburg-Vorpommern, forming part of the lake landscape around the city of Schwerin.
  • 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_69d381c04fe08190957c26c526a3b05a completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4fb9df6fc8190830f405ef955d64b completed April 7, 2026, 12:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69d979fa05d8819087e2167cc9247598 completed April 10, 2026, 10:30 p.m.
Created at: April 6, 2026, 12:15 p.m.