Triple

T388265
Position Surface form Disambiguated ID Type / Status
Subject Carl Linnaeus E8823 entity
Predicate workLocation P7 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: [Carl Linnaeus, workLocation, Uppsala]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Uppsala
Context triple: [Carl Linnaeus, workLocation, 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. 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.
  • C. Linköping
    Linköping is a major city in southern Sweden known for its university, high-tech industry, and historic cathedral.
  • D. Stockholm
    Stockholm is the capital city of Sweden, renowned for its historic architecture, cultural institutions, and role as a major political, economic, and scientific center in Scandinavia.
  • E. Östersund
    Östersund is a city in central Sweden known for its strong winter sports tradition and repeated bids to host the Winter Olympics.
  • 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_69a2e7f55c60819097aff65ea2ca2832 completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2ec5988708190aa86d9460cecf050 completed Feb. 28, 2026, 1:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69a40ad425a881909eea63c64a683c0f completed March 1, 2026, 9:45 a.m.
Created at: Feb. 28, 2026, 1:08 p.m.