Triple

T3882396
Position Surface form Disambiguated ID Type / Status
Subject European route E6 E92854 entity
Predicate passesThrough P225 FINISHED
Object Halland County E340055 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: Halland County | Statement: [European route E6, passesThrough, Halland County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Halland County
Context triple: [European route E6, passesThrough, Halland County]
  • A. Halland County chosen
    Halland County is a coastal county in southwestern Sweden known for its beaches along the Kattegat, agriculture, and proximity to the city of Gothenburg.
  • B. Kalmar County
    Kalmar County is an administrative region in southeastern Sweden that includes parts of the mainland and the island of Öland, known for its coastal landscapes and historical sites.
  • C. Viken county
    Viken county is an administrative region in southeastern Norway that includes several municipalities and borders Sweden and the Oslofjord.
  • D. Linn County
    Linn County is a county in western Oregon known for its timber industry, agriculture, and location in the Willamette Valley.
  • E. Door County
    Door County is a popular vacation destination in northeastern Wisconsin known for its scenic Lake Michigan shoreline, charming small towns, and numerous islands and lighthouses.
  • 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_69aed9697de0819087c2559295ff3d12 completed March 9, 2026, 2:30 p.m.
NER Named-entity recognition batch_69aeec8e8b3481909617ca0e37f8a6d4 completed March 9, 2026, 3:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69b52845684c8190b6f0676319a6fc3c completed March 14, 2026, 9:20 a.m.
Created at: March 9, 2026, 3:20 p.m.