Triple

T7685533
Position Surface form Disambiguated ID Type / Status
Subject Faculty of Pharmacy, Uppsala University E174106 entity
Predicate locatedIn P40 FINISHED
Object Uppland E110264 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: Uppland | Statement: [Faculty of Pharmacy, Uppsala University, locatedIn, Uppland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Uppland
Context triple: [Faculty of Pharmacy, Uppsala University, locatedIn, Uppland]
  • A. Uppland chosen
    Uppland is a historical province in east-central Sweden that includes parts of the greater Stockholm area and key infrastructure such as Stockholm Arlanda Airport.
  • B. Dalsland
    Dalsland is a historical province in western Sweden known for its forests, lakes, and rural landscapes.
  • C. Bohuslän
    Bohuslän is a coastal province in western Sweden known for its rugged granite shoreline, fishing villages, and archipelago along the Skagerrak.
  • D. Botkyrka region
    The Botkyrka region is a municipality in Stockholm County, Sweden, known for its cultural diversity and historical association with the medieval saint Botvid.
  • E. Ångermanland
    Ångermanland is a historical province in northern Sweden known for its deep river valleys, forested landscapes, and coastal areas along 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_69c6995840408190a19de6c51090f46f completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c7022118908190a3a93cfda79be0a4 completed March 27, 2026, 10:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8c7b042c8819098e345be61bbe943 completed March 29, 2026, 6:33 a.m.
Created at: March 27, 2026, 4:02 p.m.