Triple
T8317563
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | WTA 1000 tournaments |
E194743
|
entity |
| Predicate | prizeMoneyLevel |
P81900
|
FINISHED |
| Object | high prize money below Grand Slams |
—
|
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: high prize money below Grand Slams | Statement: [WTA 1000 tournaments, prizeMoneyLevel, high prize money below Grand Slams]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: prizeMoneyLevel Context triple: [WTA 1000 tournaments, prizeMoneyLevel, high prize money below Grand Slams]
-
A.
prizeMoneyCurrency
Indicates the currency in which the prize money is denominated or paid.
-
B.
hasPrizeMoney
Indicates that an entity awards, offers, or is associated with a specified amount of prize money.
-
C.
equalPrizeMoneySince
Indicates that the prize money awarded has been the same for the referenced parties starting from a specific point in time.
-
D.
prizeType
Indicates the specific category or kind of prize associated with an entity or event.
-
E.
typicalAwardAmount
Indicates the usual or most common amount of an award given in this relationship.
- 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_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. |
| PDg | Predicate description generation | batch_69cb77690720819099de1e22b84a9563 |
completed | March 31, 2026, 7:27 a.m. |
Created at: March 30, 2026, 5:55 p.m.