Triple
T29034244
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Antonio Giovinazzi |
E737808
|
entity |
| Predicate | startedKarting |
P120089
|
FINISHED |
| Object | as a child in Italy |
—
|
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: as a child in Italy | Statement: [Antonio Giovinazzi, startedKarting, as a child in Italy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: startedKarting Context triple: [Antonio Giovinazzi, startedKarting, as a child in Italy]
-
A.
kartingBackground
chosen
Indicates that an entity has experience, history, or involvement in kart racing as a foundational motorsport activity.
-
B.
hasKartingTrack
Indicates that one entity possesses or includes a karting track as a facility or feature.
-
C.
startedRacing
Indicates that an entity began participating in a racing activity or competition, marking the initiation of its involvement in racing.
-
D.
startedRacingAtAge
Indicates that an entity began participating in racing activities at a specified age.
-
E.
beganSkating
Indicates that an entity initiated the activity of skating at a particular point in time.
- 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_69f077ef00fc81909325f084ad37c035 |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69fe21b0cba48190b56c39e9f1c0eafa |
completed | May 8, 2026, 5:47 p.m. |
| PD | Predicate disambiguation | batch_69fe204576848190aecf204e2adba5dc |
completed | May 8, 2026, 5:41 p.m. |
Created at: April 28, 2026, 9:57 a.m.