Triple

T18059943
Position Surface form Disambiguated ID Type / Status
Subject Klarabergsviadukten E432143 entity
Predicate connects P390 FINISHED
Object Vasagatan 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: Vasagatan | Statement: [Klarabergsviadukten, connects, Vasagatan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vasagatan
Context triple: [Klarabergsviadukten, connects, Vasagatan]
  • A. Vasagatan chosen
    Vasagatan is a major central street in Stockholm, Sweden, known for its busy traffic, shops, and proximity to Stockholm Central Station.
  • B. Stora Värtan
    Stora Värtan is a bay of the Baltic Sea in the Stockholm archipelago, known for its coastal residential areas, marinas, and recreational boating.
  • C. Vesle
    The Vesle is a river in northeastern France that flows through the Champagne region and was a significant geographic feature during World War I battles.
  • D. Byälven
    Byälven is a river in western Sweden that flows into Lake Vänern, contributing significantly to its water system.
  • E. Dalälven
    Dalälven is a major river in central Sweden known for its extensive watershed, hydroelectric power stations, and rich natural and recreational 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_69d8b9070cac81909fa9473fb1c3f1c7 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4c10583648190a161c58abf4853d5 completed April 19, 2026, 11:48 a.m.
Created at: April 10, 2026, 10:26 a.m.