Triple

T1561013
Position Surface form Disambiguated ID Type / Status
Subject Oslofjord E33322 entity
Predicate adjacentToCity P5707 FINISHED
Object Sarpsborg E50822 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: Sarpsborg | Statement: [Oslofjord, adjacentToCity, Sarpsborg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sarpsborg
Context triple: [Oslofjord, adjacentToCity, Sarpsborg]
  • A. Sarpsborg chosen
    Sarpsborg is a historic city and municipality in Viken county, Norway, known as one of the country’s oldest towns and an important industrial and administrative center in the Østfold region.
  • 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. Risør
    Risør is a small coastal town in southern Norway known for its well-preserved wooden houses, maritime heritage, and annual wooden boat festival.
  • D. Elverum
    Elverum is a town and municipality in Innlandet county in eastern Norway, known for its forestry, military camp, and role in Norwegian World War II history.
  • E. Steinkjer
    Steinkjer is a town and municipality in central Norway that serves as an important regional center and administrative hub in Trøndelag county.
  • 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_69a885ef9cf48190b0af0f5ce3d02231 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a9088710a881909a1226e4b54311b8 completed March 5, 2026, 4:37 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae1fb8b14c8190abbcc24f17fa8243 completed March 9, 2026, 1:17 a.m.
Created at: March 4, 2026, 7:27 p.m.