Triple
T6666449
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jeffrey Maier interference play |
E151614
|
entity |
| Predicate | umpireCrewRole |
P72341
|
FINISHED |
| Object | right-field umpire |
—
|
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: right-field umpire | Statement: [Jeffrey Maier interference play, umpireCrewRole, right-field umpire]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: umpireCrewRole Context triple: [Jeffrey Maier interference play, umpireCrewRole, right-field umpire]
-
A.
umpireCrewChief
Indicates that one entity serves as the crew chief (lead umpire) for a particular umpire crew.
-
B.
umpireCrewSize
Indicates the number of umpires assigned to work together as a crew for a particular game or event.
-
C.
umpires
Indicates that an entity serves as the umpire overseeing, judging, or officiating an event, activity, or interaction involving another entity.
-
D.
umpiresProvidedBy
Indicates that one entity supplies or assigns umpires to officiate for another entity or event.
-
E.
umpireLeague
Indicates that an umpire is associated with, works in, or officiates for a particular league.
- 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_69c687f71fc081909dbd45d6377f6045 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6ce738fe88190a5557900efeec7ec |
completed | March 27, 2026, 6:37 p.m. |
| PD | Predicate disambiguation | batch_69c6ad09974c81908784300ae218961f |
completed | March 27, 2026, 4:15 p.m. |
| PDg | Predicate description generation | batch_69c6ce72809c8190be85f6e42ca1c8ea |
completed | March 27, 2026, 6:37 p.m. |
Created at: March 27, 2026, 2:02 p.m.