Triple
T9256944
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ryan Sweeting |
E222467
|
entity |
| Predicate | careerHighATPsinglesRanking |
P50351
|
FINISHED |
| Object | 64 |
—
|
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: 64 | Statement: [Ryan Sweeting, careerHighATPsinglesRanking, 64]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: careerHighATPsinglesRanking Context triple: [Ryan Sweeting, careerHighATPsinglesRanking, 64]
-
A.
highestSinglesRanking
chosen
Indicates the relationship where a specific singles ranking represents the best (numerically highest) singles position an entity has ever achieved.
-
B.
ATPsinglesTitles
Indicates the number of ATP-level singles titles a tennis player has won in professional tournaments.
-
C.
dateOfHighestSinglesRanking
Indicates the specific date on which an entity achieved its highest-ever singles ranking.
-
D.
careerSinglesTitles
Indicates the total number of singles titles an individual has won over the course of their entire professional career.
-
E.
formerWorldNo1
Indicates that the subject was ranked number one in the world in the past, but does not hold that top ranking currently.
- 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_69ca841e4cd481908e738c74e958eaea |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd06b4e2048190af0d65b904677c36 |
completed | April 1, 2026, 11:51 a.m. |
| PD | Predicate disambiguation | batch_69cc7a4e79e48190b3200247f4624867 |
completed | April 1, 2026, 1:52 a.m. |
Created at: March 30, 2026, 7:32 p.m.