Triple
T23013013
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Danica Patrick |
E572956
|
entity |
| Predicate | bestDaytona500FinishYear |
P68990
|
FINISHED |
| Object | 2013 |
—
|
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: 2013 | Statement: [Danica Patrick, bestDaytona500FinishYear, 2013]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bestDaytona500FinishYear Context triple: [Danica Patrick, bestDaytona500FinishYear, 2013]
-
A.
NASCARCupSeriesBestPointsFinish
Indicates the highest (best) overall points standing a driver has ever achieved in the NASCAR Cup Series.
-
B.
yearOfDaytona500Win
chosen
Indicates the specific year in which an entity won the Daytona 500 race.
-
C.
NASCARCupSeriesBestPointsFinishSeason
Indicates the season in which an entity achieved its highest-ever points finish in the NASCAR Cup Series standings.
-
D.
Daytona500Wins
Indicates that the subject has won the Daytona 500 race the specified number of times or in the specified instances.
-
E.
wonIndianapolis500InYear
Indicates that the subject achieved victory in the Indianapolis 500 automobile race in the specified year.
- 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_69e245b764cc8190a51be76f1d9611e1 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f183e300008190bb12c6388a8b3280 |
completed | April 29, 2026, 4:06 a.m. |
| PD | Predicate disambiguation | batch_69ef3b9cd5488190bcd23183179f48cd |
completed | April 27, 2026, 10:34 a.m. |
Created at: April 17, 2026, 3:51 p.m.