Triple
T22333432
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FIBA Basketball World Cup MVP 2019 |
E552080
|
entity |
| Predicate | winnerAssistsPerGameApprox |
P147796
|
FINISHED |
| Object | 6.0 |
—
|
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: 6.0 | Statement: [FIBA Basketball World Cup MVP 2019, winnerAssistsPerGameApprox, 6.0]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: winnerAssistsPerGameApprox Context triple: [FIBA Basketball World Cup MVP 2019, winnerAssistsPerGameApprox, 6.0]
-
A.
topAssistsAssistsPerGame
Indicates that the subject ranks among the top performers in terms of average assists made per game.
-
B.
MVPAssists
Indicates that one entity, recognized as the most valuable player (MVP), provides assistance or support to another entity in achieving a goal or outcome.
-
C.
scoredAssists
Indicates that one entity contributed an assist that led to another entity scoring (typically in a game or sports context).
-
D.
assistsLeaderTeam
Indicates that an entity provides help or support to the leader’s team in carrying out its activities or responsibilities.
-
E.
assistsInNBA
Indicates a relationship where one entity provides an assist to another entity during an NBA game or within the context of NBA play.
- 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_69e11e482f788190b78d1588fc26d606 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f1577cdcb08190a760e195c1051adb |
completed | April 29, 2026, 12:57 a.m. |
| PD | Predicate disambiguation | batch_69e73004d9e88190bb862319a5aea06b |
completed | April 21, 2026, 8:06 a.m. |
| PDg | Predicate description generation | batch_69e7342ce08c8190bc0a7085f4a952e7 |
completed | April 21, 2026, 8:24 a.m. |
Created at: April 16, 2026, 8:43 p.m.