Triple
T21731504
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Beast |
E536415
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Kings Island |
—
|
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: Kings Island | Statement: [The Beast, locatedIn, Kings Island]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kings Island Context triple: [The Beast, locatedIn, Kings Island]
-
A.
Kings Island
chosen
Kings Island is a large amusement and theme park in Mason, Ohio, known for its roller coasters and family attractions.
-
B.
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.
-
C.
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.
-
D.
Cedar Point
Cedar Point is a natural area within Jacksonville, Florida, known for its coastal habitats, hiking trails, and wildlife viewing opportunities.
-
E.
Kings Dominion
Kings Dominion is a large amusement and theme park in Doswell, Virginia, known for its roller coasters and family 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_69e0c46d3284819099a4f9d5a704eb95 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69effd0713c48190a38b3963cb3cbaf0 |
completed | April 28, 2026, 12:19 a.m. |
Created at: April 16, 2026, 6:48 p.m.