Triple

T2005910
Position Surface form Disambiguated ID Type / Status
Subject Lysaker Bridge E43583 entity
Predicate crosses P416 FINISHED
Object Lysakerelva E227159 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: Lysakerelva | Statement: [Lysaker Bridge, crosses, Lysakerelva]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lysakerelva
Context triple: [Lysaker Bridge, crosses, Lysakerelva]
  • A. Lysakerelva chosen
    Lysakerelva is a river in the Oslo area of Norway that forms part of the boundary between the municipalities of Oslo and Bærum and is known for its waterfalls, hiking paths, and historical industrial sites.
  • B. Drammenselva
    Drammenselva is a major river in southeastern Norway known for its historical timber floating, hydroelectric power production, and salmon fishing.
  • C. Nordre Ål
    Nordre Ål is a residential district in the town of Lillehammer in Innlandet county, Norway.
  • D. Beisfjordelva river
    Beisfjordelva river is a Norwegian river in Nordland county that flows through the Beisfjord area before emptying into the Ofotfjord.
  • E. Søre Ål
    Søre Ål is a residential district in the town of Lillehammer in Innlandet county, Norway.
  • 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_69a88715dbbc8190b2299e29e955d997 completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abb898795481909920c1a4c4d62c2d completed March 7, 2026, 5:33 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae1fe068ac8190b0999e4f881d134a completed March 9, 2026, 1:18 a.m.
Created at: March 4, 2026, 7:37 p.m.