Triple

T12494844
Position Surface form Disambiguated ID Type / Status
Subject Gamlebyen (Old Town) E298656 entity
Predicate locatedIn P40 FINISHED
Object 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: Fredrikstad | Statement: [Gamlebyen (Old Town), locatedIn, Fredrikstad]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fredrikstad
Context triple: [Gamlebyen (Old Town), locatedIn, 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. Porsgrunn
    Porsgrunn is an industrial and port city in Telemark county in southeastern Norway, known for its porcelain production and location along the Telemark Canal.
  • 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. Kristiansand
    Kristiansand is a coastal city in southern Norway known for its harbor, beaches, and role as a regional cultural and economic center.
  • E. Sandefjord
    Sandefjord is a coastal town and municipality in southern Norway known for its maritime heritage, whaling history, and popular seaside attractions.
  • 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_69d6ada377208190a36011199a4d8558 completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94de4089c8190917a45365e641437 completed April 10, 2026, 7:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69f65eaabadc81908f8af6bc10ce3238 completed May 2, 2026, 8:29 p.m.
Created at: April 8, 2026, 9:56 p.m.