Triple
T4140380
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alex Bregman |
E89255
|
entity |
| Predicate | fieldingRole |
P25449
|
FINISHED |
| Object | infield |
—
|
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: infield | Statement: [Alex Bregman, fieldingRole, infield]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fieldingRole Context triple: [Alex Bregman, fieldingRole, infield]
-
A.
fieldingSpecialty
chosen
Indicates a player's particular area of expertise or primary role when performing defensive (fielding) duties in a sport.
-
B.
fielderMittFeature
Indicates that a baseball fielder’s mitt possesses or includes a particular feature or characteristic.
-
C.
fielded
Indicates that an entity deployed, presented, or put forward another entity (such as a person, team, or resource) for participation or use in a particular context or activity.
-
D.
defensiveRole
Indicates that an entity serves a protective or guarding function in relation to another entity or context.
-
E.
BabeRuthRole
Indicates that an entity holds the specific role or position associated with Babe Ruth (e.g., as a legendary baseball player or cultural figure) in relation to 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_69aed95785788190ae75bcf0cd1cafdf |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af03a0f3408190adba7a8513bd3d12 |
completed | March 9, 2026, 5:30 p.m. |
| PD | Predicate disambiguation | batch_69af018a54848190987f18c066c75068 |
completed | March 9, 2026, 5:21 p.m. |
Created at: March 9, 2026, 3:43 p.m.