Triple
T2573536
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Power conferences |
E57717
|
entity |
| Predicate | recruitingImpact |
P10833
|
FINISHED |
| Object | attract majority of top high school football recruits |
—
|
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: attract majority of top high school football recruits | Statement: [Power conferences, recruitingImpact, attract majority of top high school football recruits]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: recruitingImpact Context triple: [Power conferences, recruitingImpact, attract majority of top high school football recruits]
-
A.
recruitmentChange
Indicates a change in the status, level, or conditions of recruitment associated with an entity or process.
-
B.
recruitmentFrom
Indicates that one entity recruits or sources members, employees, or participants from another entity.
-
C.
recruitmentBase
Indicates the foundational source, location, or context from which recruitment efforts or recruited entities originate.
-
D.
recruitingScope
chosen
Indicates the extent or boundaries within which recruiting activities are conducted or targeted.
-
E.
recruitedAs
Indicates that one entity has been brought into a role, position, or organization by another through a recruitment process.
- 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_69ab4a51410081908501dcf8bad9adc4 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd38792288190a39420cab126bf03 |
completed | March 7, 2026, 7:28 a.m. |
| PD | Predicate disambiguation | batch_69abd0ce4dcc8190b17a65abf9bd1bb0 |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:48 p.m.