Triple
T10418077
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Giants–Washington rivalry |
E245571
|
entity |
| Predicate | highestScoringGameWinningScore |
P17025
|
FINISHED |
| Object | 72 |
—
|
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: 72 | Statement: [Giants–Washington rivalry, highestScoringGameWinningScore, 72]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: highestScoringGameWinningScore Context triple: [Giants–Washington rivalry, highestScoringGameWinningScore, 72]
-
A.
recordHighScoringForWinner
chosen
Indicates that a record is kept of the highest score achieved by the winning entity in a given context or event.
-
B.
gameWinningScoreBy
Indicates that a particular score is the decisive amount by which a game is won by an entity.
-
C.
gameWinningScore
Indicates that a particular score results in winning the game.
-
D.
championshipGameScore
Indicates the final score achieved by each participant in a championship game.
-
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_69d381be340c8190b05998703d42d224 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4ea2938188190a908316d0a0959be |
completed | April 7, 2026, 11:27 a.m. |
| PD | Predicate disambiguation | batch_69d4dfb9d3648190aaabed901f22a8c0 |
completed | April 7, 2026, 10:43 a.m. |
Created at: April 6, 2026, 12:11 p.m.