Triple
T36734258
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Giovanna Amati |
E907423
|
entity |
| Predicate | numberOfF1GrandsPrixStarted |
P52122
|
FINISHED |
| Object | 0 |
—
|
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: 0 | Statement: [Giovanna Amati, numberOfF1GrandsPrixStarted, 0]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfF1GrandsPrixStarted Context triple: [Giovanna Amati, numberOfF1GrandsPrixStarted, 0]
-
A.
totalFormulaOneStarts
chosen
Indicates the total number of times an entity has started in Formula One races.
-
B.
grandPrixNumberInHistory
Indicates the ordinal position of a particular Grand Prix within the overall historical sequence of all Grand Prix events.
-
C.
numberOfF1WorldChampionships
Indicates the number of Formula 1 World Championship titles that an entity has won.
-
D.
hadGrandPrix
Indicates that a particular Grand Prix event took place as part of, or was hosted by, a given competition, season, or venue.
-
E.
hasGrandPrixStatus
Indicates that an event or competition holds official Grand Prix classification or status.
- 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_69f76e75aa6881909b844d00a3888ee5 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a037c8e2c648190a65fc9c7872861af |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a0e039481908a4a2666f76c5363 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:12 p.m.