Triple
T1054195
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Incredible Hulk Coaster |
E22764
|
entity |
| Predicate | capacityPerHour |
P22949
|
FINISHED |
| Object | 1920 riders |
—
|
LITERAL 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: 1920 riders | Statement: [The Incredible Hulk Coaster, capacityPerHour, 1920 riders]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: capacityPerHour Context triple: [The Incredible Hulk Coaster, capacityPerHour, 1920 riders]
-
A.
annualCapacity
Indicates the maximum amount of output or throughput an entity can produce or handle within a one-year period.
-
B.
typicalCapacity
Indicates the usual or standard amount, volume, or capability that something is designed or expected to hold, handle, or perform under normal conditions.
-
C.
totalCapacity
Indicates the maximum amount or volume that something can hold or accommodate in total.
-
D.
lawnCapacity
Indicates the maximum number of entities that can be accommodated or present on a given lawn at one time.
-
E.
seatingCapacity
Indicates the maximum number of people that something (typically a venue or vehicle) is designed or allowed to seat.
- F. None of above. chosen
Provenance (4 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_69a493da02e081908c13ff5e02a0fe7a |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b8d669448190955507e2e4975b9f |
completed | March 1, 2026, 10:08 p.m. |
| PD | Predicate disambiguation | batch_69a4b731e25c8190b5ea8466648c2c9a |
completed | March 1, 2026, 10:01 p.m. |
| PDg | Predicate description generation | batch_69a4b7da38888190a118ef20ce4ae9aa |
completed | March 1, 2026, 10:04 p.m. |
Created at: March 1, 2026, 7:42 p.m.