Triple
T17625903
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bruce Froemming |
E429841
|
entity |
| Predicate | totalMLBGamesUmpired |
P19298
|
FINISHED |
| Object | 5000+ |
—
|
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: 5000+ | Statement: [Bruce Froemming, totalMLBGamesUmpired, 5000+]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: totalMLBGamesUmpired Context triple: [Bruce Froemming, totalMLBGamesUmpired, 5000+]
-
A.
numberOfMLBGamesUmpired
chosen
Indicates the total count of Major League Baseball games that a given umpire has officiated.
-
B.
numberOfGamesPlayedInMLB
Indicates the total count of games an entity has participated in within Major League Baseball.
-
C.
numberOfWorldSeriesUmpired
Indicates the count of World Series games or series that a given umpire has officiated.
-
D.
numberOfOffFieldUmpires
Indicates the count of umpires assigned to officiate a game from positions off the field of play.
-
E.
worldSeriesUmpiringRecord
Indicates the record of a person's participation as an umpire in World Series games, including details such as years and number of series officiated.
- 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_69d889e37f308190a6aa0a69daff86c7 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e46dbc62e88190b9757dc7c52d7fee |
completed | April 19, 2026, 5:53 a.m. |
| PD | Predicate disambiguation | batch_69e3cdd7da34819099bc9481c5a79bab |
completed | April 18, 2026, 6:30 p.m. |
Created at: April 10, 2026, 5:52 a.m.