Triple

T5098095
Position Surface form Disambiguated ID Type / Status
Subject Møre og Romsdal E114915 entity
Predicate containsSettlement P847 FINISHED
Object Rauma
Rauma is a municipality in western Norway known for its dramatic fjord and mountain landscapes, including the Romsdalen valley and Trollveggen cliff.
 E494776 NE FINISHED

How this triple was built (4 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: Rauma | Statement: [Møre og Romsdal, containsSettlement, Rauma]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Rauma
Context triple: [Møre og Romsdal, containsSettlement, Rauma]
  • A. Rauma
    Rauma is a coastal town in western Finland known for its well-preserved wooden Old Town, a UNESCO World Heritage Site, and its maritime and industrial heritage.
  • B. Kauriala
    Kauriala is an alternative name for the Ghaghara, a major Himalayan river that flows through Nepal and northern India before joining the Ganges.
  • C. Imatra
    Imatra is a town and municipality in southeastern Finland known for its industrial history, proximity to the Russian border, and the Imatrankoski rapids.
  • D. Ruokolahti
    Ruokolahti is a rural municipality in South Karelia, southeastern Finland, known for its lake-rich landscapes and proximity to the Russian border.
  • E. Kerava
    Kerava is a small city in southern Finland known as a commuter town within the Greater Helsinki region.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Rauma
Triple: [Møre og Romsdal, containsSettlement, Rauma]
Generated description
Rauma is a municipality in western Norway known for its dramatic fjord and mountain landscapes, including the Romsdalen valley and Trollveggen cliff.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Rauma
Target entity description: Rauma is a municipality in western Norway known for its dramatic fjord and mountain landscapes, including the Romsdalen valley and Trollveggen cliff.
  • A. Rauma
    Rauma is a coastal town in western Finland known for its well-preserved wooden Old Town, a UNESCO World Heritage Site, and its maritime and industrial heritage.
  • B. Kauriala
    Kauriala is an alternative name for the Ghaghara, a major Himalayan river that flows through Nepal and northern India before joining the Ganges.
  • C. Imatra
    Imatra is a town and municipality in southeastern Finland known for its industrial history, proximity to the Russian border, and the Imatrankoski rapids.
  • D. Ruokolahti
    Ruokolahti is a rural municipality in South Karelia, southeastern Finland, known for its lake-rich landscapes and proximity to the Russian border.
  • E. Kerava
    Kerava is a small city in southern Finland known as a commuter town within the Greater Helsinki region.
  • F. None of above. chosen

Provenance (5 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.
NEDg Description generation batch_69bebc65f37c819088077a02c5a2939e completed March 21, 2026, 3:42 p.m.
NED2 Entity disambiguation (via description) batch_69bebcc8ad2481909ec38247b32dfdb0 completed March 21, 2026, 3:44 p.m.
Created at: March 20, 2026, 1:40 p.m.