Triple

T3367697
Position Surface form Disambiguated ID Type / Status
Subject Øresund E70875 entity
Predicate bridgeConnects P36619 FINISHED
Object Malmö E298741 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: Malmö | Statement: [Øresund, bridgeConnects, Malmö]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Malmö
Context triple: [Øresund, bridgeConnects, Malmö]
  • A. Malmö chosen
    Malmö is a major coastal city in southern Sweden known for its historic center, modern architecture like the Turning Torso, and its role as a cultural and economic hub connected to Copenhagen via the Öresund Bridge.
  • B. Sundsvall
    Sundsvall is a coastal city in central Sweden known as an important industrial and commercial center on the Gulf of Bothnia.
  • C. Gothenburg
    Gothenburg is Sweden’s second-largest city, a major port on the country’s west coast known for its maritime heritage, universities, and vibrant cultural scene.
  • D. Örebro
    Örebro is a historic city in central Sweden known for its medieval castle, university, and role as a regional economic and cultural hub.
  • E. Halmstad
    Halmstad is a coastal city in southwestern Sweden known for its historic town center, harbor, and role as a strategic site in Scandinavian conflicts.
  • 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_69ad85a729d48190afd789cd8417f289 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb2890480819082fe2e3c2874cece completed March 8, 2026, 5:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5d035d97081908688d63527fd0f66 completed March 14, 2026, 9:16 p.m.
Created at: March 8, 2026, 3:13 p.m.