Triple
T23435282
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Victoria Azarenka |
E563442
|
entity |
| Predicate | hasWonWtaSinglesTitles |
P72457
|
FINISHED |
| Object | multiple |
—
|
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: multiple | Statement: [Victoria Azarenka, hasWonWtaSinglesTitles, multiple]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWonWtaSinglesTitles Context triple: [Victoria Azarenka, hasWonWtaSinglesTitles, multiple]
-
A.
careerSinglesTitles
chosen
Indicates the total number of singles titles an individual has won over the course of their entire professional career.
-
B.
wonWimbledonSingles
Indicates that an entity has won the Wimbledon tennis tournament in the singles category.
-
C.
WTAdebutYear
Indicates the year in which a player first competed in a Women’s Tennis Association (WTA) event at the professional level.
-
D.
grandSlamFinalistInSingles
Indicates that a person has reached the final round of a Grand Slam tennis tournament in singles competition.
-
E.
wimbledonSinglesTitles
Indicates the number of Wimbledon singles championship titles an entity has won.
- 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_69e24553980c8190bb66a2ae0bdab125 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f1a5dbdf248190a09e971f2718d01f |
completed | April 29, 2026, 6:31 a.m. |
| PD | Predicate disambiguation | batch_69f061f92da081908e7f1d0cd1e9b01c |
completed | April 28, 2026, 7:30 a.m. |
Created at: April 17, 2026, 5:50 p.m.