Triple
T7828722
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Basketball Tournament |
E181310
|
entity |
| Predicate | formerTopPrize |
P79241
|
FINISHED |
| Object | 2,000,000 USD |
—
|
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: 2,000,000 USD | Statement: [The Basketball Tournament, formerTopPrize, 2,000,000 USD]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: formerTopPrize Context triple: [The Basketball Tournament, formerTopPrize, 2,000,000 USD]
-
A.
isPrizedFor
Indicates that something is highly valued or esteemed because of a particular quality, feature, or benefit it provides.
-
B.
formerHighest
Indicates that an entity once held the highest rank, position, or status in a given context but no longer does.
-
C.
prizeOfficialName
Indicates the formal, officially recognized name assigned to a prize.
-
D.
lastAwarded
Indicates the most recent time or instance at which an entity received a particular award.
-
E.
mostAwardsHolder
Indicates that the subject is the entity that holds the highest number of awards within a given group or context.
- 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_69ca8282ccec819083c48efb72d21cf9 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb04aaed1881908e1da129a43ef9c7 |
completed | March 30, 2026, 11:18 p.m. |
| PD | Predicate disambiguation | batch_69cae91ae008819098e56bbe51143b31 |
completed | March 30, 2026, 9:20 p.m. |
| PDg | Predicate description generation | batch_69caf7855a3c81908b9318f7186fc0c0 |
completed | March 30, 2026, 10:21 p.m. |
Created at: March 30, 2026, 4:43 p.m.