Triple
T23848246
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1990 National League Championship Series |
E592082
|
entity |
| Predicate | winningGames |
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: [1990 National League Championship Series, winningGames, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: winningGames Context triple: [1990 National League Championship Series, winningGames, 4]
-
A.
gamesWonBy
chosen
Indicates the number of games that have been won by a particular entity in a given context.
-
B.
seriesWinningGame
Indicates that a particular game is the decisive or clinching game in which one side wins the overall series.
-
C.
winningGameNumber
Indicates the specific game number in a series or sequence that results in a win for a given participant or side.
-
D.
mostGamesWonBy
Indicates that one entity holds the record for having won the greatest number of games compared to others in a given context.
-
E.
numberOfWins
Indicates the count of times an entity has achieved victory in a relevant context 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_69e25d221d908190b9b502ad31e66a3f |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1c9851f988190af39f57f9b71da03 |
completed | April 29, 2026, 9:04 a.m. |
| PD | Predicate disambiguation | batch_69f1614612b481908c45d99e588882f9 |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 8:10 p.m.