Triple
T37633321
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | WeatherTech Raceway Laguna Seca |
E936413
|
entity |
| Predicate | hasTurn |
P188545
|
FINISHED |
| Object | The Corkscrew |
—
|
NE NERFINISHED |
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: The Corkscrew | Statement: [WeatherTech Raceway Laguna Seca, hasTurn, The Corkscrew]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTurn Context triple: [WeatherTech Raceway Laguna Seca, hasTurn, The Corkscrew]
-
A.
hasTurnStructure
Indicates that an interaction, game, or process is organized into discrete turns that participants take in a defined order.
-
B.
hasRound
Indicates that an entity possesses, includes, or is associated with a particular round (e.g., a round of an event, game, or process).
-
C.
hasOpponentAction
Indicates that one entity performs an action that is in opposition or direct competition to the action of another entity.
-
D.
hasPlayer
Indicates that an entity (such as a team, game, or roster) includes or is associated with a specific player.
-
E.
hasTurningMethod
Indicates that an entity employs or is associated with a specific method or technique for turning or rotating something.
- 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_69f76ed24820819081bafd36e9088701 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fbaa19e4a88190b04f26c0d4e708fd |
completed | May 6, 2026, 8:52 p.m. |
| PD | Predicate disambiguation | batch_69fba8860f98819080b7bab05837b974 |
completed | May 6, 2026, 8:45 p.m. |
| PDg | Predicate description generation | batch_69fbaa108ee48190b84d13df3ef3e365 |
completed | May 6, 2026, 8:52 p.m. |
Created at: May 3, 2026, 4:18 p.m.