Triple
T17321730
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2012 United States Grand Prix |
E420576
|
entity |
| Predicate | returnedF1ToCountryAfterYears |
P126983
|
FINISHED |
| Object | 5 |
—
|
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: 5 | Statement: [2012 United States Grand Prix, returnedF1ToCountryAfterYears, 5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: returnedF1ToCountryAfterYears Context triple: [2012 United States Grand Prix, returnedF1ToCountryAfterYears, 5]
-
A.
timeInCountry
Indicates the duration or amount of time that an entity spends or has spent within a particular country.
-
B.
rejoinedCountryYear
Indicates the year in which an entity re-entered or rejoined a particular country after having previously left or been separated from it.
-
C.
returnedFromChinaYear
Indicates the year in which an entity came back from China.
-
D.
yearOfReturnToRussia
Indicates the specific year in which an entity returned to Russia after having been away.
-
E.
hasCountry
Indicates that one entity possesses, is associated with, or is located within a specific country.
- 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_69d889d22b848190a4663d0b8f8f76e7 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e439cf5394819089bff5f8dc2e8241 |
completed | April 19, 2026, 2:11 a.m. |
| PD | Predicate disambiguation | batch_69e3b01b9d1c8190a406dd941c9b11a1 |
completed | April 18, 2026, 4:23 p.m. |
| PDg | Predicate description generation | batch_69e3b2a225b08190a50f984caa6513b9 |
completed | April 18, 2026, 4:34 p.m. |
Created at: April 10, 2026, 5:43 a.m.