Triple

T14621231
Position Surface form Disambiguated ID Type / Status
Subject Low Furness E343225 entity
Predicate containsSettlement P847 FINISHED
Object Yarlside
Yarlside is a small settlement in the Low Furness area of Cumbria in North West England.
E1352133 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: Yarlside | Statement: [Low Furness, containsSettlement, Yarlside]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yarlside
Context triple: [Low Furness, containsSettlement, Yarlside]
  • A. Yiewsley
    Yiewsley is a suburban area in the London Borough of Hillingdon in west London, known for its residential character and proximity to waterways and transport links.
  • B. Snaresbrook
    Snaresbrook is a suburban area in East London known for its leafy residential streets, proximity to Epping Forest, and its Central line Underground station.
  • C. Kentish Town
    Kentish Town is a residential and commercial district in north London known for its vibrant high street, music venues, and proximity to central London.
  • D. Buckhurst Hill
    Buckhurst Hill is a suburban town in Essex, England, situated on the edge of Epping Forest and forming part of the London commuter belt.
  • E. Gants Hill
    Gants Hill is a suburban district in northeast London known for its busy road junction, Underground station on the Central line, and mix of residential and commercial areas.
  • 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: Yarlside
Triple: [Low Furness, containsSettlement, Yarlside]
Generated description
Yarlside is a small settlement in the Low Furness area of Cumbria in North West England.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Yarlside
Target entity description: Yarlside is a small settlement in the Low Furness area of Cumbria in North West England.
  • A. Yiewsley
    Yiewsley is a suburban area in the London Borough of Hillingdon in west London, known for its residential character and proximity to waterways and transport links.
  • B. Snaresbrook
    Snaresbrook is a suburban area in East London known for its leafy residential streets, proximity to Epping Forest, and its Central line Underground station.
  • C. Kentish Town
    Kentish Town is a residential and commercial district in north London known for its vibrant high street, music venues, and proximity to central London.
  • D. Buckhurst Hill
    Buckhurst Hill is a suburban town in Essex, England, situated on the edge of Epping Forest and forming part of the London commuter belt.
  • E. Gants Hill
    Gants Hill is a suburban district in northeast London known for its busy road junction, Underground station on the Central line, and mix of residential and commercial areas.
  • 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_69d822dffc3c8190aa173b90761bffda completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb466a61c81908a110d40fb959b6f completed April 14, 2026, 9:40 p.m.
NED1 Entity disambiguation (via context triple) batch_6a05ad1d53ac81908677f4188fd49cb4 completed May 14, 2026, 11:08 a.m.
NEDg Description generation batch_6a05aedf05c4819096ac6a61ada4b310 completed May 14, 2026, 11:15 a.m.
NED2 Entity disambiguation (via description) batch_6a05afe523208190a97142cd8e3b887b completed May 14, 2026, 11:20 a.m.
Created at: April 10, 2026, 1:25 a.m.