Triple
T19689785
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Italian Grand Prix |
E472803
|
entity |
| Predicate | lapsAtMonza |
P136935
|
FINISHED |
| Object | 53 |
—
|
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: 53 | Statement: [Italian Grand Prix, lapsAtMonza, 53]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lapsAtMonza Context triple: [Italian Grand Prix, lapsAtMonza, 53]
-
A.
lapsAtAlbertPark
Indicates that an entity completes or records laps at the Albert Park circuit.
-
B.
MonacoGrandPrixLocation
Indicates that a specified location is the venue where the Monaco Grand Prix takes place.
-
C.
hasPitLane
Indicates that a racing circuit, track, or similar facility includes a designated pit lane area for vehicle servicing and related activities.
-
D.
activeInFormulaOneUntil
Indicates that an entity participated as an active competitor in Formula One up to and including a specified end time or season.
-
E.
hadGrandPrix
Indicates that a particular Grand Prix event took place as part of, or was hosted by, a given competition, season, or venue.
- 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_69d8e515bef88190bc30781aea50537a |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6420f1a0c8190ae59aa0ab3ff2802 |
completed | April 20, 2026, 3:11 p.m. |
| PD | Predicate disambiguation | batch_69e53039ea808190a9106a53f564ab92 |
completed | April 19, 2026, 7:42 p.m. |
| PDg | Predicate description generation | batch_69e532bbedf081908d801600e2af94a7 |
completed | April 19, 2026, 7:53 p.m. |
Created at: April 10, 2026, 1:45 p.m.