Triple
T28210767
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lleyton Hewitt |
E711159
|
entity |
| Predicate | careerHighestATPsinglesRanking |
P50351
|
FINISHED |
| Object | 1 |
—
|
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: 1 | Statement: [Lleyton Hewitt, careerHighestATPsinglesRanking, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: careerHighestATPsinglesRanking Context triple: [Lleyton Hewitt, careerHighestATPsinglesRanking, 1]
-
A.
highestSinglesRanking
chosen
Indicates the relationship where a specific singles ranking represents the best (numerically highest) singles position an entity has ever achieved.
-
B.
yearOfHighestSinglesRanking
Indicates the specific year in which an entity achieved its highest-ever singles ranking.
-
C.
dateOfHighestSinglesRanking
Indicates the specific date on which an entity achieved its highest-ever singles ranking.
-
D.
ATPsinglesTitles
Indicates the number of ATP-level singles titles a tennis player has won in professional tournaments.
-
E.
worldNumberOneRankingAchieved
Indicates that an entity has attained the top position in a recognized world ranking within a specific field or domain.
- 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_69efb51cb5288190818c1f63a266af11 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_69f64311726c81909e7b0211ec3f9058 |
completed | May 2, 2026, 6:31 p.m. |
| PD | Predicate disambiguation | batch_69f63c6c1a948190b68c0f92c264cc0c |
completed | May 2, 2026, 6:03 p.m. |
Created at: April 27, 2026, 10:39 p.m.