Triple

T11037787
Position Surface form Disambiguated ID Type / Status
Subject Strängnäs Cathedral E260931 entity
Predicate locatedIn P40 FINISHED
Object Strängnäs E176028 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: Strängnäs | Statement: [Strängnäs Cathedral, locatedIn, Strängnäs]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Strängnäs
Context triple: [Strängnäs Cathedral, locatedIn, Strängnäs]
  • A. Strängnäs chosen
    Strängnäs is a historic Swedish town known for its medieval cathedral and picturesque location on the shores of Lake Mälaren.
  • B. Nässjö
    Nässjö is a small Swedish town in Jönköping County known as a regional railway hub and service center in southern Sweden.
  • C. Hållnäs
    Hållnäs is a rural coastal locality and peninsula in eastern Sweden known for its forests, farmland, and Baltic Sea shoreline within Tierp Municipality in Uppsala County.
  • D. Tärnsjö
    Tärnsjö is a small locality in central Sweden known for its rural setting and traditional leather tanning industry.
  • E. Nykvarn
    Nykvarn is a small locality in eastern Sweden that serves as the administrative and population center of Nykvarn Municipality in Stockholm County.
  • 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_69d6aa979bdc8190bf0e79104cc098c1 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d797fd5fe081908af13835b18de7b8 completed April 9, 2026, 12:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69e3a9c669608190af97c461beaf9f31 completed April 18, 2026, 3:56 p.m.
Created at: April 8, 2026, 9:25 p.m.