Triple

T11615781
Position Surface form Disambiguated ID Type / Status
Subject Haldenvassdraget E275502 entity
Predicate hasPart P35 FINISHED
Object Rødenessjøen E271083 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: Rødenessjøen | Statement: [Haldenvassdraget, hasPart, Rødenessjøen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rødenessjøen
Context triple: [Haldenvassdraget, hasPart, Rødenessjøen]
  • A. Rødenessjøen chosen
    Rødenessjøen is a lake in Norway known for its scenic natural surroundings and recreational opportunities such as fishing and boating.
  • B. Hurdalssjøen
    Hurdalssjøen is a large freshwater lake in eastern Norway, known for its scenic surroundings and recreational activities such as swimming, fishing, and boating.
  • C. Øymarksjøen
    Øymarksjøen is a lake in southeastern Norway known for its forested surroundings, recreational fishing, and role in the local waterway system near the Swedish border.
  • D. Norsjø
    Norsjø is a large lake in Telemark, Eastern Norway, known as an important part of the Telemark Canal waterway system.
  • E. Sandnessjøen
    Sandnessjøen is a coastal town in northern Norway known as a regional hub for the Helgeland area, with strong ties to maritime industries and access to the surrounding archipelago and mountains.
  • 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_69d6aaf84b548190ac072e4fb89ae18f completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a04675e08190837a3717242fd0f9 completed April 10, 2026, 7:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69ee872ee03481908a9d779a44ec5236 completed April 26, 2026, 9:44 p.m.
Created at: April 8, 2026, 9:38 p.m.