Triple
T25462595
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rod Laver |
E638089
|
entity |
| Predicate | hasWonWimbledonSinglesTitles |
P9287
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [Rod Laver, hasWonWimbledonSinglesTitles, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWonWimbledonSinglesTitles Context triple: [Rod Laver, hasWonWimbledonSinglesTitles, 4]
-
A.
wimbledonSinglesTitles
chosen
Indicates the number of Wimbledon singles championship titles an entity has won.
-
B.
wonWimbledonSingles
Indicates that an entity has won the Wimbledon tennis tournament in the singles category.
-
C.
consecutiveWimbledonSinglesTitles
Indicates that one entity has won Wimbledon singles titles in consecutive years.
-
D.
WimbledonSinglesFinals
Indicates that the entities are participants in the singles final match of the Wimbledon tennis tournament.
-
E.
grandSlamBestResultWimbledonSinglesYears
Indicates the years in which an entity achieved its best singles result at the Wimbledon Grand Slam tournament.
- 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_69e75db8bab08190baca80b4a8c315fd |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f6978fe97081908fe568091ad9b159 |
completed | May 3, 2026, 12:32 a.m. |
| PD | Predicate disambiguation | batch_69f69661e6ec8190948251c7516a32ad |
completed | May 3, 2026, 12:27 a.m. |
Created at: April 21, 2026, 2:12 p.m.