Triple

T11639732
Position Surface form Disambiguated ID Type / Status
Subject Tromsø Municipality E276627 entity
Predicate hasTunnel P21069 FINISHED
Object Tromsøysund Tunnel E280132 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: Tromsøysund Tunnel | Statement: [Tromsø Municipality, hasTunnel, Tromsøysund Tunnel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tromsøysund Tunnel
Context triple: [Tromsø Municipality, hasTunnel, Tromsøysund Tunnel]
  • A. Tromsøysund Tunnel chosen
    Tromsøysund Tunnel is an undersea road tunnel in northern Norway that connects the island city of Tromsø to the mainland.
  • B. Finnøy Tunnel
    The Finnøy Tunnel is an undersea road tunnel in Norway that connects the island of Finnøy to the mainland road network.
  • C. Bømlafjord Tunnel
    Bømlafjord Tunnel is a subsea road tunnel in Vestland county, Norway, forming part of the fixed link connection between the island municipality of Bømlo and the mainland.
  • D. Lærdal Tunnel
    The Lærdal Tunnel is a 24.5-kilometer road tunnel in Norway, renowned as one of the world's longest road tunnels and a key link between Oslo and Bergen.
  • E. Oslo Tunnel
    The Oslo Tunnel is a central railway tunnel in Oslo, Norway, that carries most of the city's mainline train traffic between its principal stations.
  • 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_69d6aafa51148190ab84940694c00235 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a25e90c08190b7fb73939a2be3d7 completed April 10, 2026, 7:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69f019075f4c81908e0cde830231b229 completed April 28, 2026, 2:18 a.m.
Created at: April 8, 2026, 9:39 p.m.