Triple
T754842
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ivy League women’s basketball |
E15530
|
entity |
| Predicate | scholarshipPolicy |
P12170
|
FINISHED |
| Object | no athletic scholarships |
—
|
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: no athletic scholarships | Statement: [Ivy League women’s basketball, scholarshipPolicy, no athletic scholarships]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scholarshipPolicy Context triple: [Ivy League women’s basketball, scholarshipPolicy, no athletic scholarships]
-
A.
financialAidPolicy
chosen
Indicates the rules or guidelines governing how financial assistance is determined, awarded, and managed.
-
B.
scholarshipType
Indicates the specific category or kind of scholarship associated with an entity.
-
C.
hasScholarships
Indicates that an entity provides, offers, or is associated with one or more scholarships to another entity.
-
D.
scholarshipEquivalency
Indicates that one scholarship is considered equal in value, coverage, or benefit to another scholarship or financial award.
-
E.
tuitionPolicy
Indicates the rules or guidelines governing how tuition is determined, charged, or managed for an educational program or institution.
- 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_69a493599a0081908da65f3407af1ef2 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a66820548190b373deb117187c2c |
completed | March 1, 2026, 8:49 p.m. |
| PD | Predicate disambiguation | batch_69a4a501c4cc81908de6d63e3d4f60d7 |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:37 p.m.