Triple

T259140
Position Surface form Disambiguated ID Type / Status
Subject Lancashire E5501 entity
Predicate hasMajorTown P316 FINISHED
Object Leyland
Leyland is a town in Lancashire, England, historically known for its vehicle manufacturing industry, particularly Leyland Motors.
E34365 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: Leyland | Statement: [Lancashire, hasMajorTown, Leyland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Leyland
Context triple: [Lancashire, hasMajorTown, Leyland]
  • A. Dudley
    Dudley is a masculine given name of English origin that has been borne by various notable figures in literature, politics, and entertainment.
  • B. Leigh
    Leigh is a given name and surname of English origin, used for all genders and often considered a variant spelling of "Lee."
  • C. Paisley
    Paisley is a large town in the west of Scotland known for its historic textile industry and as the origin of the famous paisley pattern.
  • D. Blackley
    Blackley is a suburban area of Manchester, England, known for its residential neighborhoods and proximity to the River Irk and local green spaces.
  • E. Coventry
    Coventry is a historic city in England, best known for its medieval cathedral destroyed in World War II and its symbolic postwar reconciliation efforts.
  • 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: Leyland
Triple: [Lancashire, hasMajorTown, Leyland]
Generated description
Leyland is a town in Lancashire, England, historically known for its vehicle manufacturing industry, particularly Leyland Motors.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Leyland
Target entity description: Leyland is a town in Lancashire, England, historically known for its vehicle manufacturing industry, particularly Leyland Motors.
  • A. Dudley
    Dudley is a masculine given name of English origin that has been borne by various notable figures in literature, politics, and entertainment.
  • B. Leigh
    Leigh is a given name and surname of English origin, used for all genders and often considered a variant spelling of "Lee."
  • C. Paisley
    Paisley is a large town in the west of Scotland known for its historic textile industry and as the origin of the famous paisley pattern.
  • D. Blackley
    Blackley is a suburban area of Manchester, England, known for its residential neighborhoods and proximity to the River Irk and local green spaces.
  • E. Coventry
    Coventry is a historic city in England, best known for its medieval cathedral destroyed in World War II and its symbolic postwar reconciliation efforts.
  • 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_69a2580a64ac8190ad76e34bb0715b5e completed Feb. 28, 2026, 2:50 a.m.
NER Named-entity recognition batch_69a25d71a10c8190894c86e7a67c5974 completed Feb. 28, 2026, 3:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69a389ab230c8190982eead1ef7b5c75 completed March 1, 2026, 12:34 a.m.
NEDg Description generation batch_69a38a0114b481908c9363e926b4b3ae completed March 1, 2026, 12:36 a.m.
NED2 Entity disambiguation (via description) batch_69a38a699a6081908c167ce9ad55a660 completed March 1, 2026, 12:38 a.m.
Created at: Feb. 28, 2026, 2:55 a.m.