Triple

T14372509
Position Surface form Disambiguated ID Type / Status
Subject Daniel Wellington E356389 entity
Predicate brandAbbreviation P36276 FINISHED
Object DW
DW is the commonly used abbreviation for Daniel Wellington, a Swedish watch and accessories brand known for its minimalist, classic designs.
 E1095397 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: DW | Statement: [Daniel Wellington, brandAbbreviation, DW]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: DW
Context triple: [Daniel Wellington, brandAbbreviation, DW]
  • A. DW
    DW is the abbreviation for Deutsche Werft AG, a former German shipbuilding company based in Hamburg.
  • B. WD
    WD is a consumer-facing brand of Western Digital known for its hard drives, solid-state drives, and other data storage products.
  • C. WD
    WD is the National Rail station code for Woodside railway station in London, England.
  • D. WD
    WD is a UK postcode area covering parts of southwest Hertfordshire and northwest Greater London, including towns such as Watford.
  • E. DEN
    DEN is the three-letter IATA airport code for Denver International Airport, the primary commercial airport serving Denver, Colorado.
  • 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: DW
Triple: [Daniel Wellington, brandAbbreviation, DW]
Generated description
DW is the commonly used abbreviation for Daniel Wellington, a Swedish watch and accessories brand known for its minimalist, classic designs.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: DW
Target entity description: DW is the commonly used abbreviation for Daniel Wellington, a Swedish watch and accessories brand known for its minimalist, classic designs.
  • A. DW
    DW is the abbreviation for Deutsche Werft AG, a former German shipbuilding company based in Hamburg.
  • B. WD
    WD is a consumer-facing brand of Western Digital known for its hard drives, solid-state drives, and other data storage products.
  • C. WD
    WD is the National Rail station code for Woodside railway station in London, England.
  • D. WD
    WD is a UK postcode area covering parts of southwest Hertfordshire and northwest Greater London, including towns such as Watford.
  • E. DEN
    DEN is the three-letter IATA airport code for Denver International Airport, the primary commercial airport serving Denver, Colorado.
  • 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_69d8279163a081908aec45c0e3f1e02f completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de8fb2082c8190b42cc5f2bab4f574 completed April 14, 2026, 7:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd4c5363a081909681b54c1d8218dc completed May 8, 2026, 2:37 a.m.
NEDg Description generation batch_69fd4e795948819097c43e30902f1654 completed May 8, 2026, 2:46 a.m.
NED2 Entity disambiguation (via description) batch_69fd4f04d7ec819095b64d4811440166 completed May 8, 2026, 2:48 a.m.
Created at: April 10, 2026, 1:15 a.m.