Triple
T35707230
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2016 Wimbledon Championships |
E1031750
|
entity |
| Predicate | boysDoublesChampions |
P183842
|
FINISHED |
| Object | Benjamin Sigouin |
—
|
NE NERFINISHED |
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: Benjamin Sigouin | Statement: [2016 Wimbledon Championships, boysDoublesChampions, Benjamin Sigouin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: boysDoublesChampions Context triple: [2016 Wimbledon Championships, boysDoublesChampions, Benjamin Sigouin]
-
A.
mixedDoublesChampions
Indicates that the related entities together won a mixed doubles championship in a given event or competition.
-
B.
WimbledonDoublesChampion
Indicates that the subject has won the doubles championship title at the Wimbledon tennis tournament.
-
C.
AustralianOpenDoublesChampion
Indicates that the subject is the winner of the doubles competition at the Australian Open tennis tournament for a given year.
-
D.
menDoublesRunnersUp
Indicates that the referenced entities were the runners-up in the men's doubles event of a competition or tournament.
-
E.
grandSlamDoublesTitles
Indicates the number of Grand Slam tennis doubles titles an entity has won.
- F. None of above. chosen
Provenance (4 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. |
| PDg | Predicate description generation | batch_69f7a34e80dc8190980d5b7b0b91341d |
completed | May 3, 2026, 7:34 p.m. |
Created at: May 3, 2026, 4:05 p.m.