Triple
T19128665
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National League 1884 season |
E468253
|
entity |
| Predicate | tieGamesCountedSeparately |
P97791
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [National League 1884 season, tieGamesCountedSeparately, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tieGamesCountedSeparately Context triple: [National League 1884 season, tieGamesCountedSeparately, true]
-
A.
tieGamesCount
Indicates the number of games in a set or series that ended in a tie, with no winner or loser.
-
B.
tieGameCountedInStandings
chosen
Indicates that tied games are included when calculating a team’s official standings or record.
-
C.
hasTieGame
Indicates that a game or match has ended with both sides having the same score, resulting in no winner.
-
D.
tieGameReason
Indicates that the specified factor or event is the reason why a particular game or match ended in a tie.
-
E.
tiebreakerGameLoser
Indicates the player or team that lost a specific tiebreaker game used to resolve a tie in a competition or match.
- 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_69d8dd0796a48190b34ce4cd9d3f3be5 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e3cf8d348190b27fc7d7d39f46f1 |
completed | April 20, 2026, 8:29 a.m. |
| PD | Predicate disambiguation | batch_69e4b9b085288190b974d649e12e0844 |
completed | April 19, 2026, 11:17 a.m. |
Created at: April 10, 2026, 12:05 p.m.