Triple
T35748268
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Evonne Goolagong Cawley |
E1033244
|
entity |
| Predicate | grandSlamDoublesAndMixedTitles |
P9285
|
FINISHED |
| Object | 7 |
—
|
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: 7 | Statement: [Evonne Goolagong Cawley, grandSlamDoublesAndMixedTitles, 7]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: grandSlamDoublesAndMixedTitles Context triple: [Evonne Goolagong Cawley, grandSlamDoublesAndMixedTitles, 7]
-
A.
grandSlamMixedDoublesTitles
Indicates the number of Grand Slam tennis titles an entity has won in mixed doubles events.
-
B.
grandSlamDoublesTitles
chosen
Indicates the number of Grand Slam tennis doubles titles an entity has won.
-
C.
grandSlamFinalsDoubles
Indicates that the entities participated as opponents or partners in the doubles final match of a Grand Slam tennis tournament.
-
D.
GrandSlamSinglesTitles
Indicates that an entity has won one or more Grand Slam singles tennis titles.
-
E.
grandSlamSinglesTitles
Indicates the number of Grand Slam singles tennis 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_69f76e119d508190a3873cb302063832 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7b5ccbda481908fe1945c35e36ce8 |
completed | May 3, 2026, 8:53 p.m. |
| PD | Predicate disambiguation | batch_69f7b4c06f5881908f0b98cad6796478 |
completed | May 3, 2026, 8:49 p.m. |
Created at: May 3, 2026, 4:06 p.m.