Triple
T8317410
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hall of Fame Open |
E194739
|
entity |
| Predicate | rankingPointsForWinner |
P7114
|
FINISHED |
| Object | 250 ATP ranking points |
—
|
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: 250 ATP ranking points | Statement: [Hall of Fame Open, rankingPointsForWinner, 250 ATP ranking points]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankingPointsForWinner Context triple: [Hall of Fame Open, rankingPointsForWinner, 250 ATP ranking points]
-
A.
rankingPoints
Indicates the number of points assigned to an entity based on its position or performance in a ranking or competition.
-
B.
positionOfWinner
Indicates the relationship that identifies which entity holds the winning position or rank in a competition or contest.
-
C.
winnerPoints
chosen
Indicates the number of points earned by the winning participant or entity in a competition or event.
-
D.
pointsForWin
Indicates the number of points awarded to an entity for achieving a win in a given context or competition.
-
E.
rarityOfWinnersByPosition
Indicates how uncommon or infrequent winners are for each specific position.
- 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_69ca82e6e2648190a31eaf6f4f757b2a |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7f630ea881909fb639383e60aee9 |
completed | March 31, 2026, 8:01 a.m. |
| PD | Predicate disambiguation | batch_69cb70bf689c8190a9d9b6b872abf53d |
completed | March 31, 2026, 6:59 a.m. |
Created at: March 30, 2026, 5:55 p.m.