Triple

T5470523
Position Surface form Disambiguated ID Type / Status
Subject Daisy Hill railway station E122819 entity
Predicate stationCode P1289 FINISHED
Object DSY
DSY is the National Rail station code for Daisy Hill railway station in Greater Manchester, England.
 E521891 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: DSY | Statement: [Daisy Hill railway station, stationCode, DSY]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: DSY
Context triple: [Daisy Hill railway station, stationCode, DSY]
  • A. DY
    DY is a UK postcode area in the West Midlands region, covering towns such as Dudley and surrounding districts.
  • B. DY
    DY is the IATA airline designator used by Norwegian Air Shuttle, a major low-cost carrier based in Norway.
  • C. DS
    DS is the standardized Diploma Supplement used across the European Higher Education Area to provide transparent, comparable information about higher education qualifications.
  • D. DS
    DS is a Microsoft multimedia framework and API used for capturing, processing, and playing audio and video streams on Windows.
  • E. DS
    DS is the Directorate of Support, a key administrative and logistical branch responsible for providing essential support services within an intelligence or governmental organization.
  • 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: DSY
Triple: [Daisy Hill railway station, stationCode, DSY]
Generated description
DSY is the National Rail station code for Daisy Hill railway station in Greater Manchester, England.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: DSY
Target entity description: DSY is the National Rail station code for Daisy Hill railway station in Greater Manchester, England.
  • A. DY
    DY is the IATA airline designator used by Norwegian Air Shuttle, a major low-cost carrier based in Norway.
  • B. DY
    DY is a UK postcode area in the West Midlands region, covering towns such as Dudley and surrounding districts.
  • C. DS
    DS is the standardized Diploma Supplement used across the European Higher Education Area to provide transparent, comparable information about higher education qualifications.
  • D. DS
    DS is the Directorate of Support, a key administrative and logistical branch responsible for providing essential support services within an intelligence or governmental organization.
  • E. DS
    DS is a Microsoft multimedia framework and API used for capturing, processing, and playing audio and video streams on Windows.
  • 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_69bd46459ff48190823377457bcf7128 completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd921b65f48190af7fcf89140f9ba8 completed March 20, 2026, 6:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf4893029081908a801c7a44872ebf completed March 22, 2026, 1:40 a.m.
NEDg Description generation batch_69bf48fd9b188190a6b880ff38b1ac67 completed March 22, 2026, 1:42 a.m.
NED2 Entity disambiguation (via description) batch_69bf496a356081909a425c14dd9c5022 completed March 22, 2026, 1:44 a.m.
Created at: March 20, 2026, 2:09 p.m.