Triple
T28210782
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lleyton Hewitt |
E711159
|
entity |
| Predicate | DavisCupTitlesWithAustralia |
P57446
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [Lleyton Hewitt, DavisCupTitlesWithAustralia, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: DavisCupTitlesWithAustralia Context triple: [Lleyton Hewitt, DavisCupTitlesWithAustralia, 2]
-
A.
davisCupTitle
chosen
Indicates that the subject has won a Davis Cup tennis title, specifying a championship victory in the Davis Cup competition.
-
B.
DavisCupFinalAppearances
Indicates the number of times an entity has reached the final round of the Davis Cup tennis competition.
-
C.
numberOfAustralianChampionships
Indicates the count of Australian Championships that an entity has won or holds.
-
D.
australianOpenSinglesTitles
Indicates the number of Australian Open singles titles one entity has won.
-
E.
ThomasCupTitle
Indicates that an entity (typically a team or country) has won the Thomas Cup championship title in badminton.
- 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.