Triple

T21371878
Position Surface form Disambiguated ID Type / Status
Subject Köping E527084 entity
Predicate hasWaterFeature P1094 FINISHED
Object Köpingsån 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: Köpingsån | Statement: [Köping, hasWaterFeature, Köpingsån]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Köpingsån
Context triple: [Köping, hasWaterFeature, Köpingsån]
  • A. Köpingsån chosen
    Köpingsån is a river in central Sweden that flows through the town of Köping before emptying into Lake Mälaren.
  • B. Munksjöån
    Munksjöån is a river in Jönköping, Sweden, that drains Lake Munksjön and flows toward Lake Vättern through the city.
  • C. Eskilstunaån
    Eskilstunaån is a river in central Sweden that drains Lake Hjälmaren and flows westward through the city of Eskilstuna toward Lake Mälaren.
  • D. Mölndalsån
    Mölndalsån is a river in western Sweden that flows through the city of Mölndal toward Gothenburg, historically important for local industry and milling.
  • E. Göta älv
    Göta älv is a major river in southwestern Sweden that flows from Lake Vänern to the Kattegat, passing through the city of Gothenburg and serving as an important waterway for transport and industry.
  • 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_69e0b51e80808190ba5cb05667af02a9 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e8b0af44d88190aedd3b2127bb297d completed April 22, 2026, 11:27 a.m.
Created at: April 16, 2026, 5:10 p.m.