Triple

T16342089
Position Surface form Disambiguated ID Type / Status
Subject Storfjorden E396830 entity
Predicate hasNearbyVillage P4647 FINISHED
Object Skodje E494777 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: Skodje | Statement: [Storfjorden, hasNearbyVillage, Skodje]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Skodje
Context triple: [Storfjorden, hasNearbyVillage, Skodje]
  • A. Skodje chosen
    Skodje is a village and former municipality in western Norway, known for its scenic fjord landscape and historic stone arch bridge.
  • B. Skrad
    Skrad is a small mountain town in Croatia’s Gorski Kotar region, known for its forested landscapes, hiking trails, and nearby natural attractions such as canyons and waterfalls.
  • C. Skorba
    Skorba is an archaeological temple site in Malta, notable for its prehistoric megalithic structures that form part of the island’s ancient temple complex heritage.
  • D. Skopin
    Skopin is a historic town in western Russia known for its traditional pottery and ceramics industry.
  • E. Kopaska
    Kopaska is the Indonesian Navy’s elite frogman and special operations unit, specializing in underwater demolition, maritime sabotage, and counter-terrorism missions.
  • 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_69d87f26864c819088365ca381a003c2 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e2da0ad510819082e440f5e2bceada completed April 18, 2026, 1:10 a.m.
NED1 Entity disambiguation (via context triple) batch_6a002dadcaa48190865cec201cde47e3 completed May 10, 2026, 7:03 a.m.
Created at: April 10, 2026, 5:07 a.m.