Triple

T10428252
Position Surface form Disambiguated ID Type / Status
Subject Hurum E245841 entity
Predicate locatedBetween P1262 FINISHED
Object Drammensfjord E461266 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: Drammensfjord | Statement: [Hurum, locatedBetween, Drammensfjord]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Drammensfjord
Context triple: [Hurum, locatedBetween, Drammensfjord]
  • A. Drammensfjord chosen
    Drammensfjord is a branch of the Oslofjord in southeastern Norway, known for its deep waters, surrounding industrial and urban areas, and role as an important maritime route.
  • B. Oslofjord
    Oslofjord is a large inlet in southeastern Norway known for its islands, coastal towns, and role as the maritime gateway to Oslo.
  • C. Eidsfjorden
    Eidsfjorden is a Norwegian fjord known for its dramatic coastal scenery and traditional fishing communities.
  • D. Skudenesfjorden
    Skudenesfjorden is a fjord in Rogaland county, southwestern Norway, lying along the coast by the island municipality of Karmøy and opening into the North Sea.
  • E. Romsdalsfjorden
    Romsdalsfjorden is a scenic fjord in Møre og Romsdal county, Norway, known for its dramatic landscapes, coastal towns, and role as a key waterway in the Romsdal region.
  • 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_69dbb6cbdd30819087c3d980ab68c44e completed April 12, 2026, 3:14 p.m.
Created at: April 6, 2026, 12:13 p.m.