Triple
T19990685
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Top Thrill Dragster |
E494054
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Cedar Point |
—
|
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: Cedar Point | Statement: [Top Thrill Dragster, locatedIn, Cedar Point]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cedar Point Context triple: [Top Thrill Dragster, locatedIn, Cedar Point]
-
A.
Cedar Point
Cedar Point is a natural area within Jacksonville, Florida, known for its coastal habitats, hiking trails, and wildlife viewing opportunities.
-
B.
Cedar Point
chosen
Cedar Point is a renowned amusement park in Sandusky, Ohio, famous for its large collection of record-breaking roller coasters and thrill rides.
-
C.
Kings Island
Kings Island is a large amusement and theme park in Mason, Ohio, known for its roller coasters and family attractions.
-
D.
King's Island
King's Island is the historic core of Limerick city, Ireland, known for landmarks like King John’s Castle and its medieval streetscape.
-
E.
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.
- 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_69da626a67648190af9653832a3aeced |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e65fe00b908190bda6b9a3a3281ec0 |
completed | April 20, 2026, 5:18 p.m. |
Created at: April 11, 2026, 3:31 p.m.