Triple
T12329938
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fred Perry |
E293931
|
entity |
| Predicate | firstWimbledonSinglesTitleYear |
P14850
|
FINISHED |
| Object | 1934 |
—
|
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: 1934 | Statement: [Fred Perry, firstWimbledonSinglesTitleYear, 1934]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstWimbledonSinglesTitleYear Context triple: [Fred Perry, firstWimbledonSinglesTitleYear, 1934]
-
A.
wimbledonSinglesTitles
Indicates the number of Wimbledon singles championship titles an entity has won.
-
B.
firstWinnerYear
chosen
Indicates the year in which an entity first won a particular competition, award, or title.
-
C.
OpenChampionshipWin
Indicates that an entity has achieved victory in an edition of the Open Championship (often known as The Open or British Open).
-
D.
grandSlamBestResultWimbledon
Indicates the best performance or highest round an entity has achieved at the Wimbledon tennis championships.
-
E.
australianOpenSinglesTitles
Indicates the number of Australian Open singles titles one 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_69d6ab6ae0dc8190b1522a9c1c55c114 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f621570819091ee1db2609233ea |
completed | April 10, 2026, 6:20 p.m. |
| PD | Predicate disambiguation | batch_69d93ec5be788190b82d2edc6a0f1095 |
completed | April 10, 2026, 6:17 p.m. |
Created at: April 8, 2026, 9:53 p.m.