Triple
T11195329
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1922 World Series title |
E264906
|
entity |
| Predicate | tieGameCountedInStandings |
P97791
|
FINISHED |
| Object | no |
—
|
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: no | Statement: [1922 World Series title, tieGameCountedInStandings, no]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tieGameCountedInStandings Context triple: [1922 World Series title, tieGameCountedInStandings, no]
-
A.
tieGamesCount
Indicates the number of games in a set or series that ended in a tie, with no winner or loser.
-
B.
hasTieGame
Indicates that a game or match has ended with both sides having the same score, resulting in no winner.
-
C.
tiebreakerGameLoser
Indicates the player or team that lost a specific tiebreaker game used to resolve a tie in a competition or match.
-
D.
matchesPlayedIn
Indicates that a particular match was played in a specified location, event, or competition context.
-
E.
fairPlayTiebreakerAffectedTeams
Indicates that the teams involved were impacted by a tiebreaker decision based on fair play criteria (such as disciplinary records).
- 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_69d6aa9eb9248190b20211772621b4bc |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8bf14e481908563b15790af4d20 |
completed | April 9, 2026, 5:58 p.m. |
| PD | Predicate disambiguation | batch_69d75cf4461c8190af84060f7db83211 |
completed | April 9, 2026, 8:01 a.m. |
| PDg | Predicate description generation | batch_69d77062271c8190b63da714ab5beff9 |
completed | April 9, 2026, 9:24 a.m. |
Created at: April 8, 2026, 9:29 p.m.