Triple
T31059815
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bill Klem |
E791499
|
entity |
| Predicate | gamesUmpiredInMajorLeagues |
P19298
|
FINISHED |
| Object | over 5,000 |
—
|
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: over 5,000 | Statement: [Bill Klem, gamesUmpiredInMajorLeagues, over 5,000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: gamesUmpiredInMajorLeagues Context triple: [Bill Klem, gamesUmpiredInMajorLeagues, over 5,000]
-
A.
associatedMajorLeague
Indicates a relationship where one entity is linked or connected to a specific Major League organization or team.
-
B.
umpireLeague
Indicates that an umpire is associated with, works in, or officiates for a particular league.
-
C.
numberOfMLBGamesUmpired
chosen
Indicates the total count of Major League Baseball games that a given umpire has officiated.
-
D.
playedInMajorLeague
Indicates that an entity has participated as a player in a major professional sports league.
-
E.
numberOfGamesPlayedInMLB
Indicates the total count of games an entity has participated in within Major League Baseball.
- 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_69f224cb08908190ba71ad9aa87518ed |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f69575e1948190b242d53f918f172a |
completed | May 3, 2026, 12:23 a.m. |
| PD | Predicate disambiguation | batch_69f690f13d7481908ddfefe95df2a1c2 |
completed | May 3, 2026, 12:04 a.m. |
Created at: April 29, 2026, 9 p.m.