Triple

T19761349
Position Surface form Disambiguated ID Type / Status
Subject SwingShot E474636 entity
Predicate themePark P4283 FINISHED
Object Kennywood NE NERFINISHED

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: Kennywood | Statement: [SwingShot, themePark, Kennywood]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kennywood
Context triple: [SwingShot, themePark, Kennywood]
  • A. Kennywood chosen
    Kennywood is a historic amusement park near Pittsburgh, Pennsylvania, known for its classic wooden roller coasters and National Historic Landmark status.
  • B. Hersheypark
    Hersheypark is a large chocolate-themed amusement park in Hershey, Pennsylvania, known for its roller coasters, family rides, and proximity to Hershey’s chocolate attractions.
  • C. Kings Island
    Kings Island is a large amusement and theme park in Mason, Ohio, known for its roller coasters and family attractions.
  • D. Dorney Park & Wildwater Kingdom
    Dorney Park & Wildwater Kingdom is a combined amusement and water park in Allentown, Pennsylvania, known for its roller coasters, family attractions, and seasonal events.
  • E. Cedar Point
    Cedar Point is a renowned amusement park in Sandusky, Ohio, famous for its large collection of record-breaking roller coasters and thrill rides.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e51a43a08190956bc6df13c91a77 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e6532004d08190944234d35e74085b completed April 20, 2026, 4:24 p.m.
Created at: April 10, 2026, 1:48 p.m.