Triple
T7929734
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Portland International Raceway |
E184157
|
entity |
| Predicate | hasLayoutType |
P10827
|
FINISHED |
| Object | road course |
—
|
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: road course | Statement: [Portland International Raceway, hasLayoutType, road course]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLayoutType Context triple: [Portland International Raceway, hasLayoutType, road course]
-
A.
hasLayout
chosen
Indicates that one entity defines or is associated with the structural arrangement or organization (layout) of another entity.
-
B.
hasLandscapeType
Indicates that an entity possesses or is characterized by a particular type or category of landscape.
-
C.
hasAlignmentType
Indicates that an entity possesses a specific alignment category or classification, such as moral, structural, or directional alignment.
-
D.
hasDisplayType
Indicates the type or category of display associated with an entity, such as the format, mode, or presentation style used to show its content.
-
E.
hasLayOrganizationType
Indicates that an entity is associated with a specific type or category of lay (non-clerical) organizational structure.
- 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_69ca828fe7bc819090f52c88dcd72183 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3acb6cb88190b4f31b7091881241 |
completed | March 31, 2026, 3:08 a.m. |
| PD | Predicate disambiguation | batch_69cae9335f288190ba96781fd6576a2b |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 5:07 p.m.