Triple
T6766643
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roberta Vinci |
E154735
|
entity |
| Predicate | dateOfCareerHighSinglesRanking |
P50352
|
FINISHED |
| Object | 2016-05-09 |
—
|
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: 2016-05-09 | Statement: [Roberta Vinci, dateOfCareerHighSinglesRanking, 2016-05-09]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dateOfCareerHighSinglesRanking Context triple: [Roberta Vinci, dateOfCareerHighSinglesRanking, 2016-05-09]
-
A.
dateOfHighestSinglesRanking
chosen
Indicates the specific date on which an entity achieved its highest-ever singles ranking.
-
B.
highestSinglesRanking
Indicates the relationship where a specific singles ranking represents the best (numerically highest) singles position an entity has ever achieved.
-
C.
yearsAsWorldNumberOne
Indicates the number of years an entity held the position of world number one in its field or ranking system.
-
D.
careerSinglesTitles
Indicates the total number of singles titles an individual has won over the course of their entire professional career.
-
E.
consecutiveWeeksAtWorldNo1
Indicates the number of weeks in a row that an entity has held the world number one ranking.
- 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_69c688109c1c8190added9a221292af0 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d2303c6881909405f0d6089dbe12 |
completed | March 27, 2026, 6:53 p.m. |
| PD | Predicate disambiguation | batch_69c6d094105881909c5806eb4afa6306 |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:12 p.m.