Triple
T49245
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Major League Baseball |
E967
|
entity |
| Predicate | umpireCrewSizeOnField |
P2307
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [Major League Baseball, umpireCrewSizeOnField, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: umpireCrewSizeOnField Context triple: [Major League Baseball, umpireCrewSizeOnField, 4]
-
A.
numberOfJudges
Indicates the total count of judges associated with a particular case, event, or entity.
-
B.
crewCountApproximate
Indicates that the relationship specifies an estimated or approximate number of crew members associated with an entity.
-
C.
numberOfParticipants
Indicates the total count of entities involved in a particular event, activity, or relationship.
-
D.
presidingOfficerForCount
Indicates that a particular officer has official responsibility for overseeing or presiding over a specific count (such as a charge, claim, or item) within a legal or procedural context.
-
E.
numberOfPersons
chosen
Indicates the total count of individual persons associated with or involved in a given entity, event, or context.
- 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_69a2480baefc81909951b14058479aa2 |
completed | Feb. 28, 2026, 1:42 a.m. |
| NER | Named-entity recognition | batch_69a24c1a5c14819088748317a3f262c8 |
completed | Feb. 28, 2026, 1:59 a.m. |
| PD | Predicate disambiguation | batch_69a24abfa7bc8190932c137a823efcb6 |
completed | Feb. 28, 2026, 1:54 a.m. |
Created at: Feb. 28, 2026, 1:47 a.m.