Triple

T15333690
Position Surface form Disambiguated ID Type / Status
Subject Hordaland E366605 entity
Predicate containsIsland P970 FINISHED
Object Bømlo E78261 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: Bømlo | Statement: [Hordaland, containsIsland, Bømlo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bømlo
Context triple: [Hordaland, containsIsland, Bømlo]
  • A. Bømlo chosen
    Bømlo is a large island and municipality in Vestland county, Norway, known for its rugged coastline, fishing communities, and extensive network of tunnels and bridges connecting it to the mainland.
  • B. Bjørnø
    Bjørnø is a small Danish island known for its tranquil rural landscape and coastal scenery in the South Funen region.
  • C. Refshaleøen
    Refshaleøen is a former industrial island in Copenhagen, Denmark, now known for its creative hubs, cultural venues, and waterfront recreational spaces.
  • D. Skarø
    Skarø is a small Danish island in the Baltic Sea known for its scenic landscapes, birdlife, and popular summer ice cream and music festival.
  • E. Jølster
    Jølster is a former municipality in Western Norway known for its scenic lakes and mountains and as the home of painter Nikolai Astrup.
  • 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_69d85a121520819093dcce999fdefe1a completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03e0268608190947a58f559a67717 completed April 16, 2026, 1:40 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff6ec2f35c8190a96af080cd7b6d0e completed May 9, 2026, 5:28 p.m.
Created at: April 10, 2026, 3:17 a.m.