Triple
T28722290
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | WTA Tour |
E730127
|
entity |
| Predicate | usesRankingPoints |
P167929
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [WTA Tour, usesRankingPoints, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesRankingPoints Context triple: [WTA Tour, usesRankingPoints, yes]
-
A.
usesRank
Indicates that one entity applies or relies on a ranking or ordered level system associated with another entity.
-
B.
hasRankingFactor
Indicates that one entity contributes as a factor to determining the ranking or ordered position of another entity.
-
C.
usesRankStructure
Indicates that an entity organizes its members or components according to a defined hierarchical rank structure.
-
D.
hasRankingUnit
Indicates that one entity is associated with a specific unit or scale used to express its ranking or ordered position.
-
E.
rankingPoints
Indicates the number of points assigned to an entity based on its position or performance in a ranking or competition.
- F. None of above. chosen
Provenance (4 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_69f043e91fe48190b73bcd8e08d433e0 |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_69f66e5f7e30819094530abceabd5f43 |
completed | May 2, 2026, 9:36 p.m. |
| PD | Predicate disambiguation | batch_69f66abfdaf08190a55f14c70be6fd4d |
completed | May 2, 2026, 9:21 p.m. |
| PDg | Predicate description generation | batch_69f66d75a8788190aa9ca2c977429045 |
completed | May 2, 2026, 9:32 p.m. |
Created at: April 28, 2026, 5:54 a.m.