Triple
T24489589
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sara Errani |
E617604
|
entity |
| Predicate | FrenchOpenDoublesChampion |
P156502
|
FINISHED |
| Object | 2012 |
—
|
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: 2012 | Statement: [Sara Errani, FrenchOpenDoublesChampion, 2012]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: FrenchOpenDoublesChampion Context triple: [Sara Errani, FrenchOpenDoublesChampion, 2012]
-
A.
grandSlamDoublesTitles
Indicates the number of Grand Slam tennis doubles titles an entity has won.
-
B.
frenchOpenSinglesTitles
Indicates the number of French Open singles titles an entity has won.
-
C.
grandSlamBestResultFrenchOpen
Indicates the best performance or highest round an entity has achieved specifically at the French Open in Grand Slam competition.
-
D.
GrandTourDoubles
Indicates a competitive doubles tennis event or match that is part of a Grand Slam (Grand Tour) tournament series.
-
E.
grandSlamFinalFrenchOpenYear
Indicates the year in which a specific French Open tennis tournament served as the final (championship) match of a Grand Slam event.
- 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_69e2d7f4e6bc8190aec540ae3b9ed7f2 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f2a9d912e88190bc39c05a9d7f407e |
completed | April 30, 2026, 1:01 a.m. |
| PD | Predicate disambiguation | batch_69f2a6a4580481908fddc385f5262f95 |
completed | April 30, 2026, 12:47 a.m. |
| PDg | Predicate description generation | batch_69f2a9d795288190916368e3cec1f666 |
completed | April 30, 2026, 1:01 a.m. |
Created at: April 18, 2026, 2:22 a.m.