Triple

T577037
Position Surface form Disambiguated ID Type / Status
Subject Fossil Group E13777 entity
Predicate brand P1500 FINISHED
Object Skagen
Skagen is a minimalist Danish-inspired watch and accessories brand known for its clean design aesthetic and modern, affordable timepieces.
 E72273 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: Skagen | Statement: [Fossil Group, brand, Skagen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Skagen
Context triple: [Fossil Group, brand, Skagen]
  • A. TAG Heuer
    TAG Heuer is a Swiss luxury watchmaker renowned for its high-end mechanical and connected timepieces that blend traditional craftsmanship with modern technology.
  • B. Braun
    Braun is a German surname most infamously associated with Eva Braun, the longtime companion and brief wife of Adolf Hitler.
  • C. Montblanc
    Montblanc is a luxury German brand renowned for its high-end writing instruments, watches, leather goods, and smartwatches.
  • D. Gillette
    Gillette is a globally recognized American brand best known for its razors and shaving products.
  • E. Bata
    Bata is a major port city on the mainland of Equatorial Guinea, serving as a key economic and transportation hub for the country.
  • 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: Skagen
Triple: [Fossil Group, brand, Skagen]
Generated description
Skagen is a minimalist Danish-inspired watch and accessories brand known for its clean design aesthetic and modern, affordable timepieces.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Skagen
Target entity description: Skagen is a minimalist Danish-inspired watch and accessories brand known for its clean design aesthetic and modern, affordable timepieces.
  • A. TAG Heuer
    TAG Heuer is a Swiss luxury watchmaker renowned for its high-end mechanical and connected timepieces that blend traditional craftsmanship with modern technology.
  • B. Braun
    Braun is a German surname most infamously associated with Eva Braun, the longtime companion and brief wife of Adolf Hitler.
  • C. Montblanc
    Montblanc is a luxury German brand renowned for its high-end writing instruments, watches, leather goods, and smartwatches.
  • D. Gillette
    Gillette is a globally recognized American brand best known for its razors and shaving products.
  • E. Bata
    Bata is a major port city on the mainland of Equatorial Guinea, serving as a key economic and transportation hub for the country.
  • 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_69a4933fa4d88190a7949cc83c08c5c1 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49b68cc808190b1ba45bdad78443d completed March 1, 2026, 8:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69a501bfb6408190bf7e1f462f39723d completed March 2, 2026, 3:19 a.m.
NEDg Description generation batch_69a5026c35408190ab22dab86c673e0f completed March 2, 2026, 3:22 a.m.
NED2 Entity disambiguation (via description) batch_69a5063ad6b481909537a97e6a81eaa4 completed March 2, 2026, 3:38 a.m.
Created at: March 1, 2026, 7:33 p.m.