Triple

T1510199
Position Surface form Disambiguated ID Type / Status
Subject Uppsala University E30374 entity
Predicate locatedIn P40 FINISHED
Object Uppsala E36359 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: Uppsala | Statement: [Uppsala University, locatedIn, Uppsala]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Uppsala
Context triple: [Uppsala University, locatedIn, Uppsala]
  • A. Uppsala chosen
    Uppsala is a historic Swedish city north of Stockholm, known for its prestigious university, medieval cathedral, and role as a cultural and ecclesiastical center.
  • B. Lund
    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 common Scandinavian surname of Swedish origin.
  • D. Nyköping
    Nyköping is a historic coastal town in southeastern Sweden known for its medieval castle, harbor, and role as a regional administrative and cultural center.
  • E. 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.
  • 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_69a885e8caf88190a5fbb6159ce87786 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a907d4edd48190a03c85e1a0cc02b1 completed March 5, 2026, 4:34 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae0aa631788190836e00b3cce934ef completed March 8, 2026, 11:47 p.m.
Created at: March 4, 2026, 7:26 p.m.