Triple

T4407446
Position Surface form Disambiguated ID Type / Status
Subject Berlin lake system E93768 entity
Predicate hasPart P35 FINISHED
Object Köpenick lake district E164184 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: Köpenick lake district | Statement: [Berlin lake system, hasPart, Köpenick lake district]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Köpenick lake district
Context triple: [Berlin lake system, hasPart, Köpenick lake district]
  • A. Amager Fælled
    Amager Fælled is a large urban nature reserve on Copenhagen’s Amager Island, known for its wetlands, meadows, and rich biodiversity amid the city.
  • B. Köpenick chosen
    Köpenick is a historic, green district in southeastern Berlin known for its old town, baroque palace on the Dahme River, and extensive forests and lakes.
  • C. Oude Pekela
    Oude Pekela is a village in the province of Groningen in the northeastern Netherlands, known historically for its peat industry and canal-side settlement.
  • D. Tegeler Insel
    Tegeler Insel is an island located within Lake Tegel in Berlin, Germany, known for its natural setting and recreational surroundings.
  • E. Tegeler Forst
    Tegeler Forst is a large forested area in the Berlin district of Tegel, known for its natural landscapes, walking trails, and recreational opportunities.
  • 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_69b345158c748190a2c040fce2da9980 completed March 12, 2026, 10:58 p.m.
NER Named-entity recognition batch_69b3548b1ca08190b3136867c7098d86 completed March 13, 2026, 12:04 a.m.
NED1 Entity disambiguation (via context triple) batch_69b5f609f7f881909d12735f4028a108 completed March 14, 2026, 11:58 p.m.
Created at: March 12, 2026, 11:28 p.m.