Triple

T6197126
Position Surface form Disambiguated ID Type / Status
Subject Vallentuna E138535 entity
Predicate hasNeighbouringLocality P68061 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: [Vallentuna, hasNeighbouringLocality, Täby]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Täby
Context triple: [Vallentuna, hasNeighbouringLocality, 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. Strängnäs
    Strängnäs is a historic Swedish town known for its medieval cathedral and picturesque location on the shores of Lake Mälaren.
  • C. Tärnsjö
    Tärnsjö is a small locality in central Sweden known for its rural setting and traditional leather tanning industry.
  • D. Strömstad
    Strömstad is a coastal town and municipality in western Sweden, near the Norwegian border, known for its archipelago, tourism, and ferry connections.
  • E. Hjulsta
    Hjulsta is a suburb in northwestern Stockholm, Sweden, known for being the terminus of one of the Stockholm metro lines.
  • 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_69c008ab9b3081908a11b2c744838435 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c062508f5c8190a00291708a9a7de9 completed March 22, 2026, 9:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69c16f2a40a88190847f607a6e2c5f4e completed March 23, 2026, 4:49 p.m.
Created at: March 22, 2026, 4:20 p.m.