Triple
T19010459
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maureen Connolly |
E465207
|
entity |
| Predicate | wonWimbledonSingles |
P134111
|
FINISHED |
| Object | 1952 |
—
|
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: 1952 | Statement: [Maureen Connolly, wonWimbledonSingles, 1952]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wonWimbledonSingles Context triple: [Maureen Connolly, wonWimbledonSingles, 1952]
-
A.
wimbledonSinglesTitles
Indicates the number of Wimbledon singles championship titles an entity has won.
-
B.
grandSlamBestResultWimbledon
Indicates the best performance or highest round an entity has achieved at the Wimbledon tennis championships.
-
C.
grandSlamFinalistInSingles
Indicates that a person has reached the final round of a Grand Slam tennis tournament in singles competition.
-
D.
wonUSOpen
Indicates that one entity achieved victory in the US Open competition or tournament over another entity or in a given year.
-
E.
grandSlamSinglesTitles
Indicates the number of Grand Slam singles tennis 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_69d8dd025c188190a1d81f5b4ec7e2c6 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d6a8225c81908e80ae7eb1c1301b |
completed | April 20, 2026, 7:32 a.m. |
| PD | Predicate disambiguation | batch_69e4a2fd80c081908237317a3a883e1c |
completed | April 19, 2026, 9:40 a.m. |
| PDg | Predicate description generation | batch_69e4ad8e075c8190ad561edc5e520057 |
completed | April 19, 2026, 10:25 a.m. |
Created at: April 10, 2026, 12:02 p.m.