Triple

T2183774
Position Surface form Disambiguated ID Type / Status
Subject Råshult, Småland, Sweden E49104 entity
Predicate hasNearbyTown P3883 FINISHED
Object Älmhult E243305 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: Älmhult | Statement: [Råshult, Småland, Sweden, hasNearbyTown, Älmhult]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Älmhult
Context triple: [Råshult, Småland, Sweden, hasNearbyTown, Älmhult]
  • A. Älmhult Municipality chosen
    Älmhult Municipality is a local government area in Kronoberg County in southern Sweden, known as the birthplace of IKEA and for its rural Småland landscapes.
  • B. Halmstad
    Halmstad is a coastal city in southwestern Sweden known for its historic town center, harbor, and role as a strategic site in Scandinavian conflicts.
  • C. Strömstad
    Strömstad is a coastal town and municipality in western Sweden, near the Norwegian border, known for its archipelago, tourism, and ferry connections.
  • D. Strängnäs
    Strängnäs is a historic Swedish town known for its medieval cathedral and picturesque location on the shores of Lake Mälaren.
  • E. Ängelholm
    Ängelholm is a coastal town in southern Sweden known for its sandy beaches, aviation museum, and scenic location at the mouth of the Rönne River.
  • 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_69a88aa72d348190a9544bb5b8a4e71d completed March 4, 2026, 7:40 p.m.
NER Named-entity recognition batch_69abbf0e92248190a9449fce4044438a completed March 7, 2026, 6 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae95f7e5448190a31dcb5ba3c547fb completed March 9, 2026, 9:42 a.m.
Created at: March 4, 2026, 7:45 p.m.