Triple

T4219235
Position Surface form Disambiguated ID Type / Status
Subject European route E16 E94297 entity
Predicate runsThrough P416 FINISHED
Object Sandvika E445026 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: Sandvika | Statement: [European route E16, runsThrough, Sandvika]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sandvika
Context triple: [European route E16, runsThrough, Sandvika]
  • A. Sandvika chosen
    Sandvika is a town in southeastern Norway that serves as the administrative center of Bærum and a commercial hub in the Greater Oslo Region.
  • B. Notodden
    Notodden is a town and municipality in Vestfold og Telemark county, Norway, known for its industrial heritage and annual blues festival.
  • C. Kristinestad
    Kristinestad is a small coastal town in western Finland known for its well-preserved wooden old town and historic maritime character.
  • D. Kongsvinger
    Kongsvinger is a town and municipality in Innlandet county, Norway, known for its historic fortress overlooking the Glomma River and its role as a regional center near the Swedish border.
  • 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_69b3451997e08190851db4a9a588837d completed March 12, 2026, 10:58 p.m.
NER Named-entity recognition batch_69b34e0b2ee08190930600e1e802b325 completed March 12, 2026, 11:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69be100f9e58819088fa92122cd57455 completed March 21, 2026, 3:27 a.m.
Created at: March 12, 2026, 11:04 p.m.