Triple

T15197456
Position Surface form Disambiguated ID Type / Status
Subject Älvsborg County E363173 entity
Predicate borderedBy P224 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: [Älvsborg County, borderedBy, Halland County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Halland County
Context triple: [Älvsborg County, borderedBy, 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. Bojnord County
    Bojnord County is an administrative division in North Khorasan Province in northeastern Iran, centered around the city of Bojnord.
  • E. Rice County
    Rice County is a county in southeastern Minnesota known for its mix of agricultural communities and college towns, including the city of Northfield.
  • 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_69d85a0b78bc8190b6e5ad51a2c4cfc5 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0067fcc788190abdc083d4eadeb36 completed April 15, 2026, 9:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69fed3342624819087be35acadd88136 completed May 9, 2026, 6:24 a.m.
Created at: April 10, 2026, 3:10 a.m.