Triple

T15693620
Position Surface form Disambiguated ID Type / Status
Subject Triangle Link E380398 entity
Predicate connects P390 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: [Triangle Link, connects, Bømlo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bømlo
Context triple: [Triangle Link, connects, 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_69d86d99e860819094b6957cde470f2c completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e04f4f5a888190bd3681bcb9bbc02f completed April 16, 2026, 2:54 a.m.
NED1 Entity disambiguation (via context triple) batch_6a009183a94081909c5892b1ccbc1d7a completed May 10, 2026, 2:09 p.m.
Created at: April 10, 2026, 4:44 a.m.