Triple
T37284460
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Don Larsen's perfect game |
E925492
|
entity |
| Predicate | runsScoredByAwayTeam |
P5831
|
FINISHED |
| Object | 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: 0 | Statement: [Don Larsen's perfect game, runsScoredByAwayTeam, 0]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: runsScoredByAwayTeam Context triple: [Don Larsen's perfect game, runsScoredByAwayTeam, 0]
-
A.
finalScoreAway
chosen
Indicates the final score achieved by the away entity (e.g., team or participant) in a contest or event.
-
B.
team2Score
Indicates the number of points or goals scored by the second team in a game or competition.
-
C.
totalRunsScored
Indicates the total number of runs that have been scored by a specified entity (such as a player or team) over a defined context or period.
-
D.
team1Score
Indicates the number of points or goals achieved by the first team in a game or competition.
-
E.
winningTeamScore
Indicates the number of points or goals achieved by the team that wins a particular game or competition.
- 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_69f76eafe20c8190856d3b996a4c31a7 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fb9e1845e881908d19158440cf3b87 |
completed | May 6, 2026, 8:01 p.m. |
| PD | Predicate disambiguation | batch_69fb8d08d6988190a00794ac26078348 |
completed | May 6, 2026, 6:48 p.m. |
Created at: May 3, 2026, 4:16 p.m.