Triple
T24971093
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ATP 500 |
E624890
|
entity |
| Predicate | rankingPointsUnit |
P33233
|
FINISHED |
| Object | 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: ATP ranking points | Statement: [ATP 500, rankingPointsUnit, ATP ranking points]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankingPointsUnit Context triple: [ATP 500, rankingPointsUnit, 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.
scoringUnit
Indicates that one entity functions as a unit or component responsible for scoring or assigning scores to another entity.
-
C.
hasRankingUnit
chosen
Indicates that one entity is associated with a specific unit or scale used to express its ranking or ordered position.
-
D.
rankingPointsRange
Indicates the range of ranking points assigned or applicable to an entity within a ranking or scoring system.
-
E.
rewardUnit
Indicates that one entity serves as the unit or measure in which a reward is quantified or granted to another entity.
- 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_69e2ff24512481908e9a72315b8d0354 |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f627aedf548190bc9f53c8a2d67b50 |
completed | May 2, 2026, 4:34 p.m. |
| PD | Predicate disambiguation | batch_69f623a4e1048190bbb8dd1253fdcee9 |
completed | May 2, 2026, 4:17 p.m. |
Created at: April 18, 2026, 6:01 a.m.