Triple

T10230205
Position Surface form Disambiguated ID Type / Status
Subject Skåne University Hospital E243318 entity
Predicate hasCampusIn P4623 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: [Skåne University Hospital, hasCampusIn, Malmö]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Malmö
Context triple: [Skåne University Hospital, hasCampusIn, 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 a small city in western Nebraska known for its historic Pony Express station and classic Midwestern agricultural community.
  • D. 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.
  • E. Örebro
    Örebro is a historic city in central Sweden known for its medieval castle, university, and role as a regional economic and cultural hub.
  • 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_69d381b0f97c819085c9b45799a5fb7c completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d20a25dc8190bd448f7ba7a13cbd completed April 7, 2026, 9:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69d7fb26d17c8190848b6b0d4df06fa2 completed April 9, 2026, 7:16 p.m.
Created at: April 6, 2026, 11:19 a.m.