Triple

T38673231
Position Surface form Disambiguated ID Type / Status
Subject Crystal Beach E943657 entity
Predicate knownFor P22 FINISHED
Object Crystal Beach Amusement Park
Crystal Beach Amusement Park was a historic lakeside amusement park in Ontario, Canada, famed for its wooden roller coasters and popularity as a summer resort destination throughout much of the 20th century.
E2280421 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: Crystal Beach Amusement Park | Statement: [Crystal Beach, knownFor, Crystal Beach Amusement Park]
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: Crystal Beach Amusement Park
Triple: [Crystal Beach, knownFor, Crystal Beach Amusement Park]
Generated description
Crystal Beach Amusement Park was a historic lakeside amusement park in Ontario, Canada, famed for its wooden roller coasters and popularity as a summer resort destination throughout much of the 20th century.

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_69f76eec28708190b9c82a505fc278e0 completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_69fcdc1665308190be24fd6749d78d85 completed May 7, 2026, 6:38 p.m.
NED1 Entity disambiguation (via context triple) batch_6a41fd6f66c88190a970b846cb134ae9 completed June 29, 2026, 5:06 a.m.
NEDg Description generation batch_6a41fe7dea008190bdba31dec4813e69 completed June 29, 2026, 5:11 a.m.
NED2 Entity disambiguation (via description) batch_6a41ff38219081908809f9918423dd0b completed June 29, 2026, 5:14 a.m.
Created at: May 3, 2026, 4:33 p.m.