Triple

T7545956
Position Surface form Disambiguated ID Type / Status
Subject Sollentuna E178401 entity
Predicate hasNeighbour P5707 FINISHED
Object Täby E20860 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: Täby | Statement: [Sollentuna, hasNeighbour, Täby]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Täby
Context triple: [Sollentuna, hasNeighbour, Täby]
  • A. Täby Municipality chosen
    Täby Municipality is a suburban local government area north of central Stockholm, Sweden, known for its affluent residential neighborhoods and strong commuter links to the capital.
  • B. Ronneby
    Ronneby is a historic town in southern Sweden known for its well-preserved wooden architecture, spa traditions, and scenic location in Blekinge County.
  • C. Strängnäs
    Strängnäs is a historic Swedish town known for its medieval cathedral and picturesque location on the shores of Lake Mälaren.
  • 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_69c69f2cbe08819088f9eb0c03ef529b completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f89963ec8190ae7b8a2b9508c074 completed March 27, 2026, 9:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69c856bb83b88190947c0efed84b891a completed March 28, 2026, 10:31 p.m.
Created at: March 27, 2026, 3:48 p.m.