Triple
T12027802
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NLE |
E286322
|
entity |
| Predicate | usesInContext |
P37480
|
FINISHED |
| Object | Major League Baseball scheduling |
—
|
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: Major League Baseball scheduling | Statement: [NLE, usesInContext, Major League Baseball scheduling]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesInContext Context triple: [NLE, usesInContext, Major League Baseball scheduling]
-
A.
areUsedIn
Indicates that certain entities serve as components, tools, or resources within a particular process, context, or application.
-
B.
usedInCase
Indicates that something (such as an item, method, or piece of information) is employed or applied within a particular case or instance.
-
C.
usedInType
Indicates that something serves as a component, element, or example within a particular type or category.
-
D.
hasTypicalUseContext
chosen
Indicates that something is commonly or characteristically used within a particular situation, setting, or context.
-
E.
usedInState
Indicates that something is employed, applied, or functions within a particular state or condition.
- 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_69d6ab4669e48190b59246358b0383ab |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9100b4ca8819084845ca4c13e34ce |
completed | April 10, 2026, 2:58 p.m. |
| PD | Predicate disambiguation | batch_69d902b6ebbc8190b13c44a61c6f81b9 |
completed | April 10, 2026, 2:01 p.m. |
Created at: April 8, 2026, 9:47 p.m.