Triple
T9962623
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | WTA 500 tournaments |
E195603
|
entity |
| Predicate | tourLevelNumber |
P25029
|
FINISHED |
| Object | second-highest regular tour level below WTA 1000 |
—
|
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: second-highest regular tour level below WTA 1000 | Statement: [WTA 500 tournaments, tourLevelNumber, second-highest regular tour level below WTA 1000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tourLevelNumber Context triple: [WTA 500 tournaments, tourLevelNumber, second-highest regular tour level below WTA 1000]
-
A.
tourLevel
chosen
Indicates the relative difficulty, expertise, or experience level associated with a particular tour or guided activity.
-
B.
teamLevel
Indicates the hierarchical rank or tier at which a team operates within an organization, competition, or structure.
-
C.
tierOfGame
Indicates the classification level or rank assigned to a game within a hierarchical system.
-
D.
trainingLevel
Indicates the degree or stage of training or skill development that an entity has attained.
-
E.
tarLevel
Indicates the degree or amount of tar associated with or produced by something in the relationship.
- 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_69ca82ebd1288190912f9e4482d1fa35 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb718cd588190a4aac48220deddec |
completed | April 2, 2026, 12:23 a.m. |
| PD | Predicate disambiguation | batch_69cd1d9ae19c819099fb3635e57c79be |
completed | April 1, 2026, 1:28 p.m. |
Created at: March 30, 2026, 8:47 p.m.