Triple
T15282444
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1978 NBA Finals |
E365302
|
entity |
| Predicate | gameCountForRunnerUp |
P43073
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [1978 NBA Finals, gameCountForRunnerUp, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: gameCountForRunnerUp Context triple: [1978 NBA Finals, gameCountForRunnerUp, 3]
-
A.
gamesWonByRunnerUp
chosen
Indicates the number of games won by the runner-up in a competition or match.
-
B.
ranjiTrophyRunnersUpCount
Indicates the number of times an entity has finished as runners-up in the Ranji Trophy cricket tournament.
-
C.
runnersUpPoints
Indicates the number of points awarded to an entity for finishing as a runner-up in a competition or ranking.
-
D.
runnerUpFinalFourCount
Indicates the number of times an entity has finished as the runner-up in a Final Four stage of a competition or tournament.
-
E.
runnerUpScore
Indicates the score achieved by the participant or entity that finished in second place in a competition or ranking.
- 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_69d85a103d9081908c1ea6c4c73ac8e3 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e00e51f82081909f63d14b589d5587 |
completed | April 15, 2026, 10:16 p.m. |
| PD | Predicate disambiguation | batch_69deca90739081909bd1b797cdb8af2b |
completed | April 14, 2026, 11:15 p.m. |
Created at: April 10, 2026, 3:15 a.m.