Triple

T10427818
Position Surface form Disambiguated ID Type / Status
Subject Halden E245830 entity
Predicate hasNeighbouringMunicipality P224 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: [Halden, hasNeighbouringMunicipality, Sarpsborg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sarpsborg
Context triple: [Halden, hasNeighbouringMunicipality, 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. Torshov
    Torshov is a residential neighborhood in Oslo, Norway, known for its early 20th-century architecture, green spaces, and vibrant local culture.
  • C. 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.
  • D. Sogndal
    Sogndal is a village and municipality in Vestland county, Norway, known for its scenic fjord landscape, agriculture, and as a regional education and service center.
  • E. Bryne
    Bryne is a town in southwestern Norway known for its agricultural surroundings and as a regional commercial center in the municipality of Time, Rogaland.
  • 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_69d381bf3dc08190bf35a2643e4e8f22 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4ea4a7dcc81909a830e08656a1c0c completed April 7, 2026, 11:28 a.m.
NED1 Entity disambiguation (via context triple) batch_69d94afc8ef0819093791447d3c3c018 completed April 10, 2026, 7:09 p.m.
Created at: April 6, 2026, 12:13 p.m.