Triple

T3701756
Position Surface form Disambiguated ID Type / Status
Subject Troms E80793 entity
Predicate containsTown P847 FINISHED
Object Gryllefjord E319757 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: Gryllefjord | Statement: [Troms, containsTown, Gryllefjord]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gryllefjord
Context triple: [Troms, containsTown, Gryllefjord]
  • A. Gryllefjord chosen
    Gryllefjord is a small coastal fishing village located on the island of Senja in northern Norway.
  • B. Sigerfjord
    Sigerfjord is a small coastal village in northern Norway, situated on the island of Hinnøya in the Vesterålen region.
  • C. Eidfjord
    Eidfjord is a small Norwegian village and municipality in Vestland county, known for its dramatic fjord landscape, waterfalls, and status as a popular cruise and tourist destination.
  • D. Lustrafjord
    Lustrafjord is a scenic inner branch of Norway’s Sognefjord, known for its dramatic mountains, clear waters, and picturesque villages.
  • E. Rekefjord
    Rekefjord is a coastal fjord and harbor area in Rogaland county, southwestern Norway, known for its maritime setting and proximity to the village of Sokndal.
  • 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_69ad8b1793888190a5f70e4b21dc05a1 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adc547c1848190a1ece46c59b7c43d completed March 8, 2026, 6:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69bd6786a558819098973b8f10b7e7cb completed March 20, 2026, 3:28 p.m.
Created at: March 8, 2026, 3:33 p.m.