Triple

T4341027
Position Surface form Disambiguated ID Type / Status
Subject Norrmalm E97578 entity
Predicate contains P35 FINISHED
Object Vasagatan E432135 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: Vasagatan | Statement: [Norrmalm, contains, Vasagatan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vasagatan
Context triple: [Norrmalm, contains, 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. Dalälven
    Dalälven is a major river in central Sweden known for its extensive watershed, hydroelectric power stations, and rich natural and recreational areas.
  • D. Ångerman River
    The Ångerman River is a major river in northern Sweden known for its long course through forested landscapes before emptying into the Gulf of Bothnia.
  • E. Veavågen
    Veavågen is a coastal village in Karmøy municipality in Rogaland county, Norway, known for its fishing industry and maritime character.
  • 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_69b3454662a481908fbcd0bbfaa3a0a4 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b35170a6648190a15ffb21640ee478 completed March 12, 2026, 11:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5e4f6643081909a2ad9a7d057ea2a completed March 14, 2026, 10:45 p.m.
Created at: March 12, 2026, 11:14 p.m.