Triple

T3184362
Position Surface form Disambiguated ID Type / Status
Subject Reddish E66664 entity
Predicate historicalCounty P1069 FINISHED
Object Lancashire E5501 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: Lancashire | Statement: [Reddish, historicalCounty, Lancashire]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lancashire
Context triple: [Reddish, historicalCounty, Lancashire]
  • A. Lancashire chosen
    Lancashire is a historic county in North West England known for its role in the Industrial Revolution and major towns such as Lancaster, Preston, and Blackpool.
  • B. Merseyside
    Merseyside is a metropolitan county in North West England that includes the city of Liverpool and its surrounding urban areas.
  • C. Cumbria
    Cumbria is a largely rural county in North West England known for its dramatic landscapes, including most of the Lake District National Park.
  • D. West Lancashire
    West Lancashire is a local government district and borough in Lancashire, England, encompassing rural villages, market towns, and parts of the West Lancashire Plain.
  • E. Yorkshire
    Yorkshire is a historic county in northern England known for its large size, distinctive cultural identity, and significant role in British political, industrial, and literary history.
  • 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_69ad8587c1bc8190a2595f2c22ee1001 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada6bfc4248190af320471688c60f0 completed March 8, 2026, 4:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69b24b777fe881909764e2f2cdb68479 completed March 12, 2026, 5:13 a.m.
Created at: March 8, 2026, 3:06 p.m.