Triple

T21769072
Position Surface form Disambiguated ID Type / Status
Subject Södermanland mainland E537373 entity
Predicate hasMajorCity P316 FINISHED
Object Strängnäs 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: Strängnäs | Statement: [Södermanland mainland, hasMajorCity, Strängnäs]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Strängnäs
Context triple: [Södermanland mainland, hasMajorCity, 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 (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_69e0c46f5d1c8190bf830409e98464e5 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69f031ac10808190837a0f69c4f8a02d completed April 28, 2026, 4:03 a.m.
Created at: April 16, 2026, 6:51 p.m.