Triple
T16145773
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daytona Beach Road Course |
E391776
|
entity |
| Predicate | layoutShape |
P121306
|
FINISHED |
| Object | roughly rectangular |
—
|
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: roughly rectangular | Statement: [Daytona Beach Road Course, layoutShape, roughly rectangular]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: layoutShape Context triple: [Daytona Beach Road Course, layoutShape, roughly rectangular]
-
A.
layoutOptions
Indicates how elements are arranged or positioned relative to each other within a given space or structure.
-
B.
layoutSupport
Indicates that one entity provides or enables structural or spatial arrangement capabilities for another entity.
-
C.
layoutEngine
Indicates the rendering or layout system responsible for arranging and positioning elements within a visual or document structure.
-
D.
frameShape
Indicates that one entity has the specified geometric or structural shape of a frame in relation to another entity.
-
E.
layoutCategory
Indicates how an entity is classified or grouped according to its layout or structural arrangement.
- 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_69d87f1c65e48190aa2b4c472e9bafc4 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e21d9376fc8190bd9ef586b00c1d3b |
completed | April 17, 2026, 11:46 a.m. |
| PD | Predicate disambiguation | batch_69e182885bc08190822ae7e8a4b8ac1f |
completed | April 17, 2026, 12:44 a.m. |
| PDg | Predicate description generation | batch_69e1835b64948190ae1d2a9d4cc64acf |
completed | April 17, 2026, 12:48 a.m. |
Created at: April 10, 2026, 5:01 a.m.