Triple

T13748553
Position Surface form Disambiguated ID Type / Status
Subject SKKN by Kim E330279 entity
Predicate hasAbbreviation P43 FINISHED
Object SKKN E330279 NE FINISHED

How this triple was built (2 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: SKKN | Statement: [SKKN by Kim, hasAbbreviation, SKKN]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: SKKN
Context triple: [SKKN by Kim, hasAbbreviation, SKKN]
  • A. SKKN by Kim chosen
    SKKN by Kim is a skincare line founded by Kim Kardashian that offers a range of high-end, minimalist beauty products focused on skin health and rejuvenation.
  • B. KKN
    KKN is the National Rail station code assigned to Kirknewton railway station in Scotland.
  • C. KKNK
    KKNK is a major annual Afrikaans-language arts and culture festival held in Oudtshoorn, South Africa, showcasing theatre, music, visual arts, and literature.
  • D. SKN
    SKN is the station code for South Kensington tube station, a major London Underground interchange serving the South Kensington area.
  • E. SMK
    SMK is the commonly used abbreviation for the Office of the Prime Minister of Norway, the central executive body that supports the Norwegian Prime Minister and coordinates government policy.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d81c573f288190aa2403d484fa3d49 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de02132a108190aca728b95e83af01 completed April 14, 2026, 9 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7a854098c8190983d142c9930962b completed May 3, 2026, 7:56 p.m.
Created at: April 9, 2026, 10:08 p.m.