Triple
T14741895
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tower of Terror II |
E346367
|
entity |
| Predicate | countryFirst |
P59622
|
FINISHED |
| Object | first roller coaster in Australia to reach 160 km/h |
—
|
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: first roller coaster in Australia to reach 160 km/h | Statement: [Tower of Terror II, countryFirst, first roller coaster in Australia to reach 160 km/h]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryFirst Context triple: [Tower of Terror II, countryFirst, first roller coaster in Australia to reach 160 km/h]
-
A.
countryStart
Indicates that an entity marks the beginning or starting point of a country-related extent, boundary, or association.
-
B.
country1
Indicates that the subject entity is a country (or represents a country) in the given context.
-
C.
country2
Indicates a secondary or alternative country associated with an entity, such as a second nationality, location, or jurisdiction.
-
D.
mainCountry
Indicates that one country is the primary or most significant country associated with a given entity or context.
-
E.
firstForCountry
chosen
Indicates that the subject is the first instance or occurrence of its type to happen or exist within the specified country.
- F. None of above.
Provenance (3 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_69d822e6f1c88190bc494d491a907114 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec7367a1c819081082cc355e385fa |
completed | April 14, 2026, 11:01 p.m. |
| PD | Predicate disambiguation | batch_69de8bf9331481909582045cd567d91f |
completed | April 14, 2026, 6:48 p.m. |
Created at: April 10, 2026, 1:30 a.m.