Triple
T20187846
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Intimidator 305 |
E492908
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Kings Dominion |
—
|
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 Dominion | Statement: [Intimidator 305, locatedIn, Kings Dominion]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kings Dominion Context triple: [Intimidator 305, locatedIn, Kings Dominion]
-
A.
Kings Dominion
chosen
Kings Dominion is a large amusement and theme park in Doswell, Virginia, 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.
Kings Island
Kings Island is a large amusement and theme park in Mason, Ohio, known for its roller coasters and family attractions.
-
D.
Phantasialand
Phantasialand is a major German theme park known for its highly themed lands and innovative roller coasters and attractions.
-
E.
Six Flags America
Six Flags America is a major amusement and theme park featuring roller coasters, water rides, and family attractions located in the Washington, D.C. metropolitan area.
- 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_69da6268a034819081cbd9ea5a1c9475 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66ad2c43c8190a2fc5ef2a0514e53 |
completed | April 20, 2026, 6:05 p.m. |
Created at: April 11, 2026, 11:37 p.m.