Triple

T6376544
Position Surface form Disambiguated ID Type / Status
Subject Götaplatsen E143479 entity
Predicate hasViewOf P854 FINISHED
Object Kungsportsavenyen E588699 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: Kungsportsavenyen | Statement: [Götaplatsen, hasViewOf, Kungsportsavenyen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kungsportsavenyen
Context triple: [Götaplatsen, hasViewOf, Kungsportsavenyen]
  • A. Kungsportsavenyen chosen
    Kungsportsavenyen is a major boulevard and central thoroughfare in Gothenburg, Sweden, known for its shops, restaurants, and cultural venues.
  • B. Vålerenggata
    Vålerenggata is a street located in the Vålerenga neighborhood of Oslo, Norway, known for its traditional wooden houses and historic urban character.
  • C. Bogstadveien
    Bogstadveien is a prominent shopping and commercial street in Oslo, Norway, known for its boutiques, cafes, and central location.
  • D. Trondheimsveien
    Trondheimsveien is a major thoroughfare in Oslo, Norway, serving as an important traffic artery through the city and its northeastern districts.
  • E. Kungsgatan
    Kungsgatan is a major central street in Stockholm, Sweden, known for its early 20th-century architecture, bustling shops, and iconic twin towers.
  • 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_69c008d9f4348190ab598a2913259a1c completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c0683bfc7081908b15c3c9a3c72e7b completed March 22, 2026, 10:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69c64badc3c481908199bf32069cc1c7 completed March 27, 2026, 9:19 a.m.
Created at: March 22, 2026, 4:33 p.m.