Triple
T1020357
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jurassic World VelociCoaster |
E22024
|
entity |
| Predicate | trainCount |
P23304
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [Jurassic World VelociCoaster, trainCount, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trainCount Context triple: [Jurassic World VelociCoaster, trainCount, 4]
-
A.
trains
Indicates that one entity teaches, instructs, or coaches another entity to develop skills, knowledge, or abilities.
-
B.
peakDailyTrains
Indicates the maximum number of trains operating per day on a given route, line, or segment during its busiest period.
-
C.
numberOfRailwayTracks
Indicates the quantity of railway tracks associated with or present at a given entity or location.
-
D.
numberOfTrainsInvolved
Indicates the count of trains that are involved in a particular event, situation, or incident.
-
E.
railwayTraffic
Indicates the presence, flow, or management of train movements along railway lines between locations.
- 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_69a493d6e380819097b384986ffc315c |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b7dd76b081909ed4d2f7adb6480d |
completed | March 1, 2026, 10:04 p.m. |
| PD | Predicate disambiguation | batch_69a4b724c7908190a5b92a57fbdbff4e |
completed | March 1, 2026, 10:01 p.m. |
| PDg | Predicate description generation | batch_69a4b7bd3d50819091e6f1d2ffe4c7ee |
completed | March 1, 2026, 10:03 p.m. |
Created at: March 1, 2026, 7:41 p.m.