Triple

T15466275
Position Surface form Disambiguated ID Type / Status
Subject Crossing Cup E372037 entity
Predicate hasCourse P6650 FINISHED
Object Baby Park E370320 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: Baby Park | Statement: [Crossing Cup, hasCourse, Baby Park]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Baby Park
Context triple: [Crossing Cup, hasCourse, Baby Park]
  • A. Baby Park chosen
    Baby Park is a chaotic, oval-shaped racetrack in the Mario Kart series known for its short laps and intense item-filled races.
  • B. Baby Cham
    Baby Cham is a Jamaican dancehall and reggae artist known for hits like "Ghetto Story" and his influential role in early-2000s dancehall music.
  • C. Baby U
    Baby U is an alias of U-God, the American rapper best known as a member of the influential hip hop group Wu-Tang Clan.
  • D. Baby Corp
    Baby Corp is the fictional, corporate-style organization of highly intelligent infants that manages baby-related operations in the Boss Baby animated film franchise.
  • E. Babyland
    Babyland is a family-friendly area within Bear Country USA where visitors can observe and learn about young and newborn animals in a safe, accessible setting.
  • 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_69d85cc8bd308190886949510b42e764 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e03f680cec8190836a5ec841dee224 completed April 16, 2026, 1:46 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff2d01a23c819095cf75b7d5a801a9 completed May 9, 2026, 12:48 p.m.
Created at: April 10, 2026, 3:33 a.m.