Triple

T5290972
Position Surface form Disambiguated ID Type / Status
Subject Hoved Line E119739 entity
Predicate terminus P388 FINISHED
Object Eidsvoll E94298 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: Eidsvoll | Statement: [Hoved Line, terminus, Eidsvoll]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Eidsvoll
Context triple: [Hoved Line, terminus, Eidsvoll]
  • A. Eidsvoll chosen
    Eidsvoll is a historic Norwegian town best known as the site where Norway’s constitution was drafted and signed in 1814.
  • B. Akershus
    Akershus is a historical county in southeastern Norway that encompassed areas around the capital Oslo and played a key role in the region’s administrative and military history.
  • C. Eidsvolls plass
    Eidsvolls plass is a central public square and park in Oslo, Norway, located in front of the Parliament building and often used for gatherings and events.
  • D. Fredrikstad
    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.
  • E. Rakkestad
    Rakkestad is a rural municipality in Viken county, southeastern Norway, known for its agriculture and forests.
  • 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_69bd446de5648190b313a90bd96730d2 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd84eac7b88190900142bd1310c0fd completed March 20, 2026, 5:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf21b22be08190ad5d3d6b12b80bcb completed March 21, 2026, 10:54 p.m.
Created at: March 20, 2026, 1:52 p.m.