Triple
T38327498
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stowe |
E1036828
|
entity |
| Predicate | hasTurnNumber |
P190646
|
FINISHED |
| Object | Turn 15 at Silverstone (modern Grand Prix layout) |
—
|
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: Turn 15 at Silverstone (modern Grand Prix layout) | Statement: [Stowe, hasTurnNumber, Turn 15 at Silverstone (modern Grand Prix layout)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTurnNumber Context triple: [Stowe, hasTurnNumber, Turn 15 at Silverstone (modern Grand Prix layout)]
-
A.
hasTurn
Indicates that a particular entity is currently the one whose move, action, or opportunity to act is due in a turn-based sequence.
-
B.
numberOfTurns
Indicates the total count of discrete turns or rotations involved in an interaction, process, or motion.
-
C.
hasTurnStructure
Indicates that an interaction, game, or process is organized into discrete turns that participants take in a defined order.
-
D.
hasRoudNumber
Indicates that an entity is associated with or assigned a specific round number within a sequence of rounds or stages.
-
E.
hasRound
Indicates that an entity possesses, includes, or is associated with a particular round (e.g., a round of an event, game, or process).
- 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_69f76e1c16fc8190bde982289dd5106b |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fccbd826708190b5fab12c4236299a |
completed | May 7, 2026, 5:28 p.m. |
| PD | Predicate disambiguation | batch_69fcc58838e08190b8fa54aa5c165f2d |
completed | May 7, 2026, 5:02 p.m. |
| PDg | Predicate description generation | batch_69fccbd6b7688190b746803cf78d5704 |
completed | May 7, 2026, 5:28 p.m. |
Created at: May 3, 2026, 4:30 p.m.