Triple
T26658274
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Floorless Coaster |
E666569
|
entity |
| Predicate | typicalInversionTypes |
P198210
|
FINISHED |
| Object | vertical loop |
—
|
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: vertical loop | Statement: [Floorless Coaster, typicalInversionTypes, vertical loop]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalInversionTypes Context triple: [Floorless Coaster, typicalInversionTypes, vertical loop]
-
A.
typicalReverseType
Indicates that the subject is the usual or canonical inverse relation type of the given predicate.
-
B.
typicalInvocations
Indicates the usual or most common ways in which an action, function, or process is called, used, or carried out.
-
C.
inversionType
Indicates the specific kind or category of inversion relationship that holds between entities, such as one being the reverse, opposite, or role-swapped form of the other.
-
D.
inversions
Indicates a relationship where the usual order, position, or hierarchy between elements is reversed or turned upside down.
-
E.
typicalIn
Indicates that something commonly occurs, appears, or is found within a given context, category, or environment.
- 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_69ee9cf8c7188190b9b00270a8a89164 |
completed | April 26, 2026, 11:17 p.m. |
| NER | Named-entity recognition | batch_69fed357b2b4819084c709056a54461f |
completed | May 9, 2026, 6:25 a.m. |
| PD | Predicate disambiguation | batch_69fed103d9cc81909b11619745110c61 |
completed | May 9, 2026, 6:15 a.m. |
| PDg | Predicate description generation | batch_69fed3569ca881909f4291baeb665d9d |
completed | May 9, 2026, 6:25 a.m. |
Created at: April 27, 2026, 2:35 a.m.