Triple

T16047572
Position Surface form Disambiguated ID Type / Status
Subject Ramsay Bolton E389262 entity
Predicate familyName P18 FINISHED
Object Snow
Snow is the surname traditionally given to illegitimate children in the North of Westeros in the "Game of Thrones" / "A Song of Ice and Fire" universe.
E649273 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: Snow | Statement: [Ramsay Bolton, familyName, Snow]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Snow
Context triple: [Ramsay Bolton, familyName, Snow]
  • A. Snow
    Snow is a white color variant of the iMac G3, known for its clean, minimalist appearance among the line’s iconic translucent and colorful designs.
  • B. Snow
    "Snow" is a notable abstract painting by British artist Howard Hodgkin, recognized for its expressive brushwork and evocative use of color to suggest memory and atmosphere.
  • C. Snow
    "Snow" is a song featured on the album *Back to Scratch* by Welsh singer-songwriter Charlotte Church.
  • D. Snow
    "Snow" is a festive song from the 1954 musical film *White Christmas*, celebrated for its nostalgic lyrics about the beauty and romance of wintertime snowfall.
  • E. Snow
    Snow is frozen atmospheric precipitation in the form of ice crystals that accumulate on the ground, often creating white, wintry landscapes.
  • 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: Snow
Triple: [Ramsay Bolton, familyName, Snow]
Generated description
Snow is the surname traditionally given to illegitimate children in the North of Westeros in the "Game of Thrones" / "A Song of Ice and Fire" universe.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Snow
Target entity description: Snow is the surname traditionally given to illegitimate children in the North of Westeros in the "Game of Thrones" / "A Song of Ice and Fire" universe.
  • A. Snow chosen
    Snow is a common English surname borne by various notable figures in literature, science, and public life.
  • B. Snow
    Snow is the fictional universe in which the manga and anime series "Ka" is set, encompassing its unique world, lore, and settings.
  • C. Snow
    Snow is frozen atmospheric precipitation in the form of ice crystals that accumulate on the ground, often creating white, wintry landscapes.
  • D. Snow
    Snow is a South Korean photo and video messaging app known for its augmented reality filters and stickers, similar in concept to Snapchat.
  • E. Snow
    Snow is a white color variant of the iMac G3, known for its clean, minimalist appearance among the line’s iconic translucent and colorful designs.
  • F. None of above.

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_69d86dae698881908327ef2d67706cb9 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1835eda348190aff492f0ff668cce completed April 17, 2026, 12:48 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffdbddc25481908fca660c4f14eaff completed May 10, 2026, 1:14 a.m.
NEDg Description generation batch_69ffdc915be88190a0e949fcee608242 completed May 10, 2026, 1:17 a.m.
NED2 Entity disambiguation (via description) batch_69ffdd17239c8190a3c0c4d146a279f7 completed May 10, 2026, 1:19 a.m.
Created at: April 10, 2026, 4:56 a.m.