Triple

T14409554
Position Surface form Disambiguated ID Type / Status
Subject Double or Nothing E357287 entity
Predicate hasPart P35 FINISHED
Object Go Legend
Go Legend is a component or segment of the "Double or Nothing" work, likely serving as a distinct chapter, mode, or feature within that larger context.
E1097075 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: Go Legend | Statement: [Double or Nothing, hasPart, Go Legend]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Go Legend
Context triple: [Double or Nothing, hasPart, Go Legend]
  • A. Racer
    Racer is a classic wooden racing roller coaster located at Kennywood amusement park in Pennsylvania.
  • B. Kart
    Kart refers to a member or native of the Kart dynasty of Herat, a medieval ruling family in the region of present-day western Afghanistan.
  • C. Racers
    The Racers are the athletic teams representing Murray State University in intercollegiate sports.
  • D. Racers
    Racers was a professional ice hockey team based in Indianapolis that competed in the World Hockey Association during the 1970s.
  • E. RC Racer
    RC Racer is a high-speed, U-shaped shuttle roller coaster themed after the remote-control car from Pixar's Toy Story films.
  • 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: Go Legend
Triple: [Double or Nothing, hasPart, Go Legend]
Generated description
Go Legend is a component or segment of the "Double or Nothing" work, likely serving as a distinct chapter, mode, or feature within that larger context.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Go Legend
Target entity description: Go Legend is a component or segment of the "Double or Nothing" work, likely serving as a distinct chapter, mode, or feature within that larger context.
  • A. Racer
    Racer is a classic wooden racing roller coaster located at Kennywood amusement park in Pennsylvania.
  • B. Kart
    Kart refers to a member or native of the Kart dynasty of Herat, a medieval ruling family in the region of present-day western Afghanistan.
  • C. Racers
    The Racers are the athletic teams representing Murray State University in intercollegiate sports.
  • D. Racers
    Racers was a professional ice hockey team based in Indianapolis that competed in the World Hockey Association during the 1970s.
  • E. RC Racer
    RC Racer is a high-speed, U-shaped shuttle roller coaster themed after the remote-control car from Pixar's Toy Story films.
  • 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_69d82793421c8190861eb0e673b085de completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de90c9b3448190aec1608836a5e913 completed April 14, 2026, 7:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd5524e26c81909424b5ba88b5f330 completed May 8, 2026, 3:14 a.m.
NEDg Description generation batch_69fd56844d7c8190906b6550fb1c28d5 completed May 8, 2026, 3:20 a.m.
NED2 Entity disambiguation (via description) batch_69fd5731c9188190bda2958bef87dfe2 completed May 8, 2026, 3:23 a.m.
Created at: April 10, 2026, 1:17 a.m.