Triple

T10230204
Position Surface form Disambiguated ID Type / Status
Subject Skåne University Hospital E243318 entity
Predicate hasCampusIn P4623 FINISHED
Object Lund E222857 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: Lund | Statement: [Skåne University Hospital, hasCampusIn, Lund]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lund
Context triple: [Skåne University Hospital, hasCampusIn, Lund]
  • A. Lund
    Lund is a common Scandinavian surname of Swedish origin.
  • B. Lund chosen
    Lund is a historic city in southern Sweden known for its medieval cathedral, prestigious university, and role as a significant cultural and academic center in Scandinavia.
  • C. Lund
    Lund is a district of the Norwegian city of Kristiansand, known for its residential areas, educational institutions, and proximity to the city center.
  • D. Lund
    Lund is a small municipality in Rogaland county in southwestern Norway, known for its rural landscapes and proximity to lakes and mountains.
  • E. Sundsvall
    Sundsvall is a coastal city in central Sweden known as an important industrial and commercial center on the Gulf of Bothnia.
  • 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_69d979d64a5481909be6d6bd1d8b6433 completed April 10, 2026, 10:29 p.m.
Created at: April 6, 2026, 11:19 a.m.