Triple

T11565557
Position Surface form Disambiguated ID Type / Status
Subject Johan Skytte E274242 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: [Johan Skytte, workLocation, Uppsala]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Uppsala
Context triple: [Johan Skytte, 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. 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 municipality in Rogaland county in southwestern Norway, known for its rural landscapes and proximity to lakes and mountains.
  • 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_69d6aae5ac3c81908d2b0a3a665665b2 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d88dd321f88190a57ecaf079fbbc3f completed April 10, 2026, 5:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69f71f03e00c819091ae5273aa10fe4b completed May 3, 2026, 10:10 a.m.
Created at: April 8, 2026, 9:37 p.m.