Triple

T12308346
Position Surface form Disambiguated ID Type / Status
Subject Kornhamnstorg E293409 entity
Predicate near P350 FINISHED
Object Järntorget E293408 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: Järntorget | Statement: [Kornhamnstorg, near, Järntorget]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Järntorget
Context triple: [Kornhamnstorg, near, Järntorget]
  • A. Järntorget chosen
    Järntorget is a historic public square in Stockholm’s Old Town, long associated with trade and iron commerce and surrounded by well-preserved medieval and early modern buildings.
  • B. Grubbegata
    Grubbegata is a street in central Oslo, Norway, known for running through the area that houses key government buildings and institutions.
  • C. Hötorget
    Hötorget is a central square in downtown Stockholm known for its market stalls, surrounding shops, and cultural venues.
  • D. Riddarhustorget
    Riddarhustorget is a historic public square in central Stockholm, Sweden, situated on the island of Gamla stan and known for its proximity to the House of Nobility and other notable 17th-century buildings.
  • E. Mårten Trotzigs gränd
    Mårten Trotzigs gränd is a famously narrow, historic alley in Stockholm’s Old Town, known as one of the tightest streets in the city and a popular tourist attraction.
  • 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_69d6ab6a2b50819082f6aedd32ed608a completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d93f01ace8819087f245b9216f4dc8 completed April 10, 2026, 6:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69f62a9d50b081908f0bdb7a2ca2832a completed May 2, 2026, 4:47 p.m.
Created at: April 8, 2026, 9:53 p.m.