Triple

T821742
Position Surface form Disambiguated ID Type / Status
Subject Lillehammer E17762 entity
Predicate locatedOnRiver P165 FINISHED
Object Lågen
Lågen is a major river in southeastern Norway that flows through the Gudbrandsdalen valley before joining the Mjøsa lake.
E98197 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: Lågen | Statement: [Lillehammer, locatedOnRiver, Lågen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lågen
Context triple: [Lillehammer, locatedOnRiver, Lågen]
  • A. Lagting
    Lagting was one of the two former chambers of the Norwegian Parliament, historically functioning as its upper house before the legislature became unicameral.
  • B. Mo i Rana
    Mo i Rana is an industrial town in Nordland county, Norway, known for its steel industry, proximity to the Arctic Circle, and role as a regional hub in Northern Norway.
  • C. Gjallarhorn
    Gjallarhorn is the resounding horn of the god Heimdall in Norse mythology, famously used to signal the onset of Ragnarök.
  • D. Berg en Dal
    Berg en Dal is a Dutch municipality in the province of Gelderland, known for its hilly landscape, forests, and proximity to the city of Nijmegen.
  • E. Skaugum
    Skaugum is the official country residence of the Norwegian royal family, located in Asker near Oslo.
  • 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: Lågen
Triple: [Lillehammer, locatedOnRiver, Lågen]
Generated description
Lågen is a major river in southeastern Norway that flows through the Gudbrandsdalen valley before joining the Mjøsa lake.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Lågen
Target entity description: Lågen is a major river in southeastern Norway that flows through the Gudbrandsdalen valley before joining the Mjøsa lake.
  • A. Lagting
    Lagting was one of the two former chambers of the Norwegian Parliament, historically functioning as its upper house before the legislature became unicameral.
  • B. Mo i Rana
    Mo i Rana is an industrial town in Nordland county, Norway, known for its steel industry, proximity to the Arctic Circle, and role as a regional hub in Northern Norway.
  • C. Gjallarhorn
    Gjallarhorn is the resounding horn of the god Heimdall in Norse mythology, famously used to signal the onset of Ragnarök.
  • D. Berg en Dal
    Berg en Dal is a Dutch municipality in the province of Gelderland, known for its hilly landscape, forests, and proximity to the city of Nijmegen.
  • E. Skaugum
    Skaugum is the official country residence of the Norwegian royal family, located in Asker near Oslo.
  • 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_69a4937bcaac8190a322524ac6f45a5a completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4ab7aea38819092a0860ec6e2a033 completed March 1, 2026, 9:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69a76d91c2948190bc13a223548facba completed March 3, 2026, 11:24 p.m.
NEDg Description generation batch_69a77e828bb08190a67768d08557f305 completed March 4, 2026, 12:36 a.m.
NED2 Entity disambiguation (via description) batch_69a77efbc2ac819083a900d2ecd8924e completed March 4, 2026, 12:38 a.m.
Created at: March 1, 2026, 7:38 p.m.