Triple
T28405982
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | WTA Tour (North American events) |
E719527
|
entity |
| Predicate | prizeMoneyAwarded |
P72606
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [WTA Tour (North American events), prizeMoneyAwarded, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: prizeMoneyAwarded Context triple: [WTA Tour (North American events), prizeMoneyAwarded, true]
-
A.
hasPrizeMoney
chosen
Indicates that an entity awards, offers, or is associated with a specified amount of prize money.
-
B.
prizeMoneyCurrency
Indicates the currency in which the prize money is denominated or paid.
-
C.
prizeMoneyLevel
Indicates the relative amount or tier of monetary reward associated with a prize or award.
-
D.
equalPrizeMoneySince
Indicates that the prize money awarded has been the same for the referenced parties starting from a specific point in time.
-
E.
awardAmount
Indicates the specific quantity or value of an award that is granted in the context of a particular awarding event or 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_69eff6f0f37c8190b37bc6fab08a9449 |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_69f64d700f70819080f54d75296f8890 |
completed | May 2, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_69f641e2f1708190b45b48d6a43c51d2 |
completed | May 2, 2026, 6:26 p.m. |
Created at: April 28, 2026, 1:23 a.m.