Triple
T6459489
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dream Team |
E142078
|
entity |
| Predicate | averageMarginOfVictory |
P71115
|
FINISHED |
| Object | approximately 44 points per game |
—
|
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: approximately 44 points per game | Statement: [Dream Team, averageMarginOfVictory, approximately 44 points per game]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: averageMarginOfVictory Context triple: [Dream Team, averageMarginOfVictory, approximately 44 points per game]
-
A.
finalRoundMargin
Indicates the point or score difference between competitors in the final round of a contest or competition.
-
B.
winningTeamScore
Indicates the number of points or goals achieved by the team that wins a particular game or competition.
-
C.
averageGoalsPerMatch
Indicates the typical number of goals scored per match in the context of the given entities or competition.
-
D.
pointsScoredByLosingTeam
Indicates the number of points scored by the team that did not win in a given game or match.
-
E.
numberOfGoals
Indicates the total count of goals scored or achieved by an entity in a given 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_69c008d2f91c8190a8178767a35e08fc |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c069f347f48190a2b22c5b648b17bd |
completed | March 22, 2026, 10:15 p.m. |
| PD | Predicate disambiguation | batch_69c0673b44148190aed70084f0ff4992 |
completed | March 22, 2026, 10:03 p.m. |
| PDg | Predicate description generation | batch_69c068cb3b888190812ed56f2fdd45ed |
completed | March 22, 2026, 10:10 p.m. |
Created at: March 22, 2026, 4:48 p.m.