Triple

T13234538
Position Surface form Disambiguated ID Type / Status
Subject Yorkshire coalfield E315109 entity
Predicate majorMiningTowns P105974 FINISHED
Object Askern
Askern is a former coal mining town in South Yorkshire, England, historically known for its colliery and later as a small commuter and residential community.
E1029681 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: Askern | Statement: [Yorkshire coalfield, majorMiningTowns, Askern]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Askern
Context triple: [Yorkshire coalfield, majorMiningTowns, Askern]
  • A. Barholm
    Barholm is a small village and civil parish in Lincolnshire, England, known for its rural character and historic parish church.
  • B. Askham
    Askham is a small village in Cumbria, England, known for its traditional stone buildings and scenic setting near the Lake District National Park.
  • C. Dechmont
    Dechmont is a small village in West Lothian, Scotland, known for its rural setting and proximity to Livingston.
  • D. Arbirlot
    Arbirlot is a small rural village in the Angus council area of eastern Scotland, known for its historic parish church and scenic countryside setting near the North Sea coast.
  • E. Dunkeld
    Dunkeld is a historic town in Perth and Kinross, Scotland, known for its picturesque setting on the River Tay and its medieval cathedral.
  • 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: Askern
Triple: [Yorkshire coalfield, majorMiningTowns, Askern]
Generated description
Askern is a former coal mining town in South Yorkshire, England, historically known for its colliery and later as a small commuter and residential community.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Askern
Target entity description: Askern is a former coal mining town in South Yorkshire, England, historically known for its colliery and later as a small commuter and residential community.
  • A. Barholm
    Barholm is a small village and civil parish in Lincolnshire, England, known for its rural character and historic parish church.
  • B. Askham
    Askham is a small village in Cumbria, England, known for its traditional stone buildings and scenic setting near the Lake District National Park.
  • C. Dechmont
    Dechmont is a small village in West Lothian, Scotland, known for its rural setting and proximity to Livingston.
  • D. Arbirlot
    Arbirlot is a small rural village in the Angus council area of eastern Scotland, known for its historic parish church and scenic countryside setting near the North Sea coast.
  • E. Dunkeld
    Dunkeld is a historic town in Perth and Kinross, Scotland, known for its picturesque setting on the River Tay and its medieval cathedral.
  • 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_69d806affc688190a25b6ccc588e9c72 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98f71c5388190a6e122e14384efd7 completed April 11, 2026, 12:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69f6ff2dca2c81909cab1aa868ad575d completed May 3, 2026, 7:54 a.m.
NEDg Description generation batch_69f70476310c8190b13dc948c1f1ce95 completed May 3, 2026, 8:16 a.m.
NED2 Entity disambiguation (via description) batch_69f70578047c819089fc3044eceb4eac completed May 3, 2026, 8:21 a.m.
Created at: April 9, 2026, 9:22 p.m.