Triple

T5098079
Position Surface form Disambiguated ID Type / Status
Subject Møre og Romsdal E114915 entity
Predicate containsSettlement P847 FINISHED
Object Sykkylven E367273 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: Sykkylven | Statement: [Møre og Romsdal, containsSettlement, Sykkylven]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sykkylven
Context triple: [Møre og Romsdal, containsSettlement, Sykkylven]
  • A. Sykkylven chosen
    Sykkylven is a municipality in Møre og Romsdal county, Norway, known for its fjord landscape and strong furniture manufacturing industry.
  • B. Bykle
    Bykle is a small rural municipality in southern Norway known for its mountainous landscapes and outdoor recreation opportunities.
  • C. Synnervika
    Synnervika is a small lakeside locality in Norway that serves as a key access point and harbor area on the shores of Lake Femunden.
  • D. Skiptvet
    Skiptvet is a rural municipality in Viken county, southeastern Norway, known for its agricultural landscape and small villages.
  • E. Stetind
    Stetind is a distinctive, obelisk-shaped granite mountain in Nordland, Norway, often called Norway’s national mountain and renowned among climbers and photographers.
  • 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_69bd443fc49c819089629c00e311310c completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd7567d21081909227ed8f08b74c71 completed March 20, 2026, 4:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69beba8529ec8190bb1e97eb1044c899 completed March 21, 2026, 3:34 p.m.
Created at: March 20, 2026, 1:40 p.m.