Triple

T730471
Position Surface form Disambiguated ID Type / Status
Subject Warrington E14818 entity
Predicate hasSuburb P747 FINISHED
Object Lymm E34787 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: Lymm | Statement: [Warrington, hasSuburb, Lymm]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lymm
Context triple: [Warrington, hasSuburb, Lymm]
  • A. Lymm chosen
    Lymm is a picturesque village in Cheshire, England, known for its historic center, scenic waterways, and surrounding countryside.
  • B. Aywick
    Aywick is a small coastal settlement on the island of Yell in Shetland, Scotland.
  • C. Royton
    Royton is a town in Greater Manchester, England, historically part of Lancashire and now within the Metropolitan Borough of Oldham.
  • D. Ribblehead
    Ribblehead is a remote hamlet in North Yorkshire, England, best known for its dramatic moorland setting and the iconic Ribblehead Viaduct on the Settle–Carlisle railway.
  • E. Pendlebury
    Pendlebury is a suburban area in the City of Salford, Greater Manchester, England, historically known for its coal mining and textile industries.
  • 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_69a4934d9930819099eed80096b0597d completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a5c290e481908497430a05dbfb90 completed March 1, 2026, 8:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69a76d742ef08190bb9405a1cde84eb1 completed March 3, 2026, 11:23 p.m.
Created at: March 1, 2026, 7:37 p.m.