Triple
T26658296
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Floorless Coaster |
E666569
|
entity |
| Predicate | typicalTrainLayout |
P198230
|
FINISHED |
| Object | multiple rows of two to four seats per row |
—
|
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: multiple rows of two to four seats per row | Statement: [Floorless Coaster, typicalTrainLayout, multiple rows of two to four seats per row]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalTrainLayout Context triple: [Floorless Coaster, typicalTrainLayout, multiple rows of two to four seats per row]
-
A.
trackLayout
Indicates how the components or segments of a track are arranged and connected in relation to one another.
-
B.
railTracks
Indicates that one entity consists of, includes, or is associated with rail tracks used for guiding trains or rail vehicles.
-
C.
stationLayout
Indicates the spatial arrangement and structural organization of elements within a station.
-
D.
trainConfiguration
Indicates the specific arrangement and composition of train elements (such as locomotives and cars) used together for a particular operation or service.
-
E.
railroadMet
Indicates that two or more railroads encountered or connected with each other at a specific place or time.
- 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_69fed48d8e148190a99c0aea29f8a3ee |
completed | May 9, 2026, 6:30 a.m. |
| PD | Predicate disambiguation | batch_69fed3c82a24819095e614e31ac0307f |
completed | May 9, 2026, 6:27 a.m. |
| PDg | Predicate description generation | batch_69fed48c92ec8190b3be88880d86de86 |
completed | May 9, 2026, 6:30 a.m. |
Created at: April 27, 2026, 2:35 a.m.