Triple

T21283103
Position Surface form Disambiguated ID Type / Status
Subject Uppsala Airport E524579 entity
Predicate serves P98 FINISHED
Object Uppsala NE NERFINISHED

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 Airport, serves, Uppsala]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Uppsala
Context triple: [Uppsala Airport, serves, 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. Karlstad
    Karlstad is a city in central Sweden known as the capital of Värmland County, situated on the northern shore of Lake Vänern.
  • C. Sundsvall
    Sundsvall is a coastal city in central Sweden known as an important industrial and commercial center on the Gulf of Bothnia.
  • D. 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.
  • E. Lund
    Lund is a small unincorporated rural community located in Iron County, Utah, historically known as a railroad stop and gateway to nearby desert regions.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b5171f6c8190a5d57201ede73811 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e736d3dfbc819081bd876d95c7c480 completed April 21, 2026, 8:35 a.m.
Created at: April 16, 2026, 4:03 p.m.