Triple

T12620946
Position Surface form Disambiguated ID Type / Status
Subject Rolvsøy E301376 entity
Predicate partOf P40 FINISHED
Object city of Fredrikstad E53030 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: city of Fredrikstad | Statement: [Rolvsøy, partOf, city of Fredrikstad]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: city of Fredrikstad
Context triple: [Rolvsøy, partOf, city of Fredrikstad]
  • A. Fredrikstad chosen
    Fredrikstad is a coastal city in southeastern Norway known for its well-preserved fortified old town and role as a regional educational and commercial center.
  • B. Trondheim
    Trondheim is a historic Norwegian city in Trøndelag county, known for its medieval Nidaros Cathedral and role as a former capital of Norway.
  • C. Stavanger
    Stavanger is a coastal city in southwestern Norway known for its oil industry hub status, historic wooden houses, and proximity to natural attractions like the Lysefjord and Preikestolen.
  • D. Eidsvoll
    Eidsvoll is a historic Norwegian town best known as the site where Norway’s constitution was drafted and signed in 1814.
  • E. Beitstad
    Beitstad was a former municipality in Trøndelag county, Norway, that later became part of the town and municipality of Steinkjer.
  • 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_69d7bdeaf49c8190b13800111fa77ea3 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d960c75c9c819092265ebc2b39f21d completed April 10, 2026, 8:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6a539f098819096e955a035742dad completed May 3, 2026, 1:30 a.m.
Created at: April 9, 2026, 5:13 p.m.