Triple
T35707161
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shingo Kunieda |
E1031749
|
entity |
| Predicate | ITFDoublesTitles |
P50354
|
FINISHED |
| Object | 70+ |
—
|
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: 70+ | Statement: [Shingo Kunieda, ITFDoublesTitles, 70+]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ITFDoublesTitles Context triple: [Shingo Kunieda, ITFDoublesTitles, 70+]
-
A.
worldTitles
Indicates that an entity has won one or more world championship titles in a given field or competition.
-
B.
careerHighDoublesRanking
Indicates the highest doubles ranking a person has achieved in their professional career.
-
C.
mixedDoublesChampions
Indicates that the related entities together won a mixed doubles championship in a given event or competition.
-
D.
mastersTitles
Indicates that one entity holds one or more master's degree titles associated with another entity (such as an institution, field, or program).
-
E.
tourDoublesTitles
chosen
Indicates the number of doubles titles a player has won on the professional tennis tour.
- 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_69f76e0d393c8190b6303c64408736db |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7a34f8ee08190a040304635539a8f |
completed | May 3, 2026, 7:34 p.m. |
| PD | Predicate disambiguation | batch_69f7a06f125c8190843af194f042a465 |
completed | May 3, 2026, 7:22 p.m. |
Created at: May 3, 2026, 4:05 p.m.