Triple

T13618975
Position Surface form Disambiguated ID Type / Status
Subject The Rainbow Stories E325397 entity
Predicate hasPart P35 FINISHED
Object The Yellow Sugar
The Yellow Sugar is a short story featured within William T. Vollmann’s collection *The Rainbow Stories*.
E1051776 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: The Yellow Sugar | Statement: [The Rainbow Stories, hasPart, The Yellow Sugar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: The Yellow Sugar
Context triple: [The Rainbow Stories, hasPart, The Yellow Sugar]
  • A. Sugar on a Stick
    Sugar on a Stick is a portable, USB-based distribution of the Sugar learning environment designed to provide children with an easy, bootable educational platform.
  • B. Pan de Azúcar
    Pan de Azúcar is a prominent snow-capped peak in Colombia’s Sierra Nevada del Cocuy, known for its striking glaciated slopes and popularity among high-altitude trekkers and climbers.
  • C. Sweeting
    Sweeting is a surname most notably associated with Bahamian-born American former professional tennis player Ryan Sweeting.
  • D. Big Sugar
    Big Sugar is a Canadian rock band known for its heavy, blues-influenced sound and fusion of rock, reggae, and dub styles.
  • E. Süßen
    Süßen is a small town in the German state of Baden-Württemberg, situated in the Fils Valley and known for its local industry and residential character.
  • 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: The Yellow Sugar
Triple: [The Rainbow Stories, hasPart, The Yellow Sugar]
Generated description
The Yellow Sugar is a short story featured within William T. Vollmann’s collection *The Rainbow Stories*.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: The Yellow Sugar
Target entity description: The Yellow Sugar is a short story featured within William T. Vollmann’s collection *The Rainbow Stories*.
  • A. Sugar on a Stick
    Sugar on a Stick is a portable, USB-based distribution of the Sugar learning environment designed to provide children with an easy, bootable educational platform.
  • B. Pan de Azúcar
    Pan de Azúcar is a prominent snow-capped peak in Colombia’s Sierra Nevada del Cocuy, known for its striking glaciated slopes and popularity among high-altitude trekkers and climbers.
  • C. Sweeting
    Sweeting is a surname most notably associated with Bahamian-born American former professional tennis player Ryan Sweeting.
  • D. Big Sugar
    Big Sugar is a Canadian rock band known for its heavy, blues-influenced sound and fusion of rock, reggae, and dub styles.
  • E. Süßen
    Süßen is a small town in the German state of Baden-Württemberg, situated in the Fils Valley and known for its local industry and residential character.
  • 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_69d8076aae28819092cf636190ee5529 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbb0ae77e0819081e3b14642460dc6 completed April 12, 2026, 2:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69f77fa0b81c819094e2fa209ef9857c completed May 3, 2026, 5:02 p.m.
NEDg Description generation batch_69f783c24d088190ad53fa2d33a255c9 completed May 3, 2026, 5:20 p.m.
NED2 Entity disambiguation (via description) batch_69f78452e8bc8190a55f2be349fe718f completed May 3, 2026, 5:22 p.m.
Created at: April 9, 2026, 9:50 p.m.