Triple
T22455724
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Connie Mack |
E555110
|
entity |
| Predicate | managedGamesRecord |
P26066
|
FINISHED |
| Object | most games managed in Major League Baseball history |
—
|
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: most games managed in Major League Baseball history | Statement: [Connie Mack, managedGamesRecord, most games managed in Major League Baseball history]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: managedGamesRecord Context triple: [Connie Mack, managedGamesRecord, most games managed in Major League Baseball history]
-
A.
managedGamesWithAngels
Indicates that a person held a managerial role in baseball games in which the Angels team participated.
-
B.
homeGamesPlayedBy
Indicates the number or set of home games that are played by a particular team or player.
-
C.
hasGamesAt
Indicates that a particular location, venue, or platform hosts or offers one or more games.
-
D.
totalGamesManaged
chosen
Indicates the total number of games that an entity has managed in its role (e.g., as a coach or manager).
-
E.
gamesOf
Indicates a relationship where one entity is the set, list, or collection of games associated with another entity.
- 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_69e11e5113208190ab58c6b595f9d1d0 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15b4f19708190a50f29598fb1a204 |
completed | April 29, 2026, 1:13 a.m. |
| PD | Predicate disambiguation | batch_69e898ad961c819098fd1e46129bddcc |
completed | April 22, 2026, 9:45 a.m. |
Created at: April 16, 2026, 8:48 p.m.