Triple
T4998626
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1956 NBA Finals |
E112308
|
entity |
| Predicate | gameCountWonByChampion |
P15130
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [1956 NBA Finals, gameCountWonByChampion, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: gameCountWonByChampion Context triple: [1956 NBA Finals, gameCountWonByChampion, 4]
-
A.
championRegularSeasonWins
Indicates that an entity is the champion based on having the highest number of regular season wins.
-
B.
championTotalWinsIncludingPostseason
Indicates the total number of games a champion has won in a season, counting both regular season and postseason victories.
-
C.
gamesWonBy
chosen
Indicates the number of games that have been won by a particular entity in a given context.
-
D.
numberOfWins
Indicates the count of times an entity has achieved victory in a relevant context or competition.
-
E.
championshipWinRate
Indicates the proportion of championships won relative to the total number of championship opportunities or appearances.
- 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_69bd4432b32c81909f3b3c6bd10f0653 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd7472a1dc8190942f568a81fdd961 |
completed | March 20, 2026, 4:23 p.m. |
| PD | Predicate disambiguation | batch_69bd714aee2481908fb0dd5fa2daf3a1 |
completed | March 20, 2026, 4:09 p.m. |
Created at: March 20, 2026, 1:34 p.m.