Triple

T2032567
Position Surface form Disambiguated ID Type / Status
Subject Windermere railway station E44550 entity
Predicate stationCode P1289 FINISHED
Object WDM
WDM is the National Rail station code for Windermere railway station in Cumbria, England.
 E225999 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: WDM | Statement: [Windermere railway station, stationCode, WDM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: WDM
Context triple: [Windermere railway station, stationCode, WDM]
  • A. DWM
    DWM is the Windows system component responsible for rendering and managing the visual effects and composition of the desktop user interface.
  • B. DWC
    DWC is the IATA airport code for Al Maktoum International Airport, a major airport in Dubai, United Arab Emirates.
  • C. Wavelengths
    Wavelengths is the Toronto International Film Festival’s avant-garde and experimental cinema program, showcasing innovative and boundary-pushing works in film and video.
  • D. WD
    WD is a consumer-facing brand of Western Digital known for its hard drives, solid-state drives, and other data storage products.
  • E. WSM
    WSM is the three-letter ISO 3166-1 alpha-3 country code assigned to Samoa.
  • 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: WDM
Triple: [Windermere railway station, stationCode, WDM]
Generated description
WDM is the National Rail station code for Windermere railway station in Cumbria, England.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: WDM
Target entity description: WDM is the National Rail station code for Windermere railway station in Cumbria, England.
  • A. DWM
    DWM is the Windows system component responsible for rendering and managing the visual effects and composition of the desktop user interface.
  • B. DWC
    DWC is the IATA airport code for Al Maktoum International Airport, a major airport in Dubai, United Arab Emirates.
  • C. Wavelengths
    Wavelengths is the Toronto International Film Festival’s avant-garde and experimental cinema program, showcasing innovative and boundary-pushing works in film and video.
  • D. WD
    WD is a consumer-facing brand of Western Digital known for its hard drives, solid-state drives, and other data storage products.
  • E. WSM
    WSM is the three-letter ISO 3166-1 alpha-3 country code assigned to Samoa.
  • 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_69a889144f2481909932f0746a93023d completed March 4, 2026, 7:33 p.m.
NER Named-entity recognition batch_69abb9313134819088133fb69b8f606f completed March 7, 2026, 5:35 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae0b02123c819094d3dc9a7c5c267a completed March 8, 2026, 11:49 p.m.
NEDg Description generation batch_69ae0b78f3fc81909010d88b454e9fa1 completed March 8, 2026, 11:51 p.m.
NED2 Entity disambiguation (via description) batch_69ae0c5983ac819082362a3b67dd9808 completed March 8, 2026, 11:55 p.m.
Created at: March 4, 2026, 7:39 p.m.