Triple

T4098714
Position Surface form Disambiguated ID Type / Status
Subject Helvellyn E87885 entity
Predicate hasRouteFrom P4374 FINISHED
Object Glenridding E128097 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: Glenridding | Statement: [Helvellyn, hasRouteFrom, Glenridding]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Glenridding
Context triple: [Helvellyn, hasRouteFrom, Glenridding]
  • A. Glenridding chosen
    Glenridding is a small lakeside village in England’s Lake District, popular as a base for walking, sailing, and exploring the surrounding fells.
  • B. Keswick
    Keswick is a historic market town and popular tourist base in England’s Lake District, known for its scenic setting near Derwentwater and surrounding fells.
  • C. Keswick
    Keswick is a suburban community within the town of Georgina in Ontario, Canada, situated along the southern shores of Lake Simcoe.
  • D. Coniston
    Coniston is a village in England’s Lake District that serves as a popular base for exploring the surrounding fells and nearby Coniston Water.
  • E. Kirkby Stephen
    Kirkby Stephen is a small market town in Cumbria, England, known for its historic architecture and scenic location near the Yorkshire Dales and Lake District.
  • 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_69aed94564cc8190a9c1457daedb6e7f completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefd0bdea48190805a79515ee92709 completed March 9, 2026, 5:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69b57f1d1ab081909b7999e8feede458 completed March 14, 2026, 3:30 p.m.
Created at: March 9, 2026, 3:40 p.m.