Triple
T793227
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NCAA women’s basketball |
E16959
|
entity |
| Predicate | primaryAgeGroup |
P2736
|
FINISHED |
| Object | 18–23-year-old student-athletes |
—
|
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: 18–23-year-old student-athletes | Statement: [NCAA women’s basketball, primaryAgeGroup, 18–23-year-old student-athletes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryAgeGroup Context triple: [NCAA women’s basketball, primaryAgeGroup, 18–23-year-old student-athletes]
-
A.
primaryIntake
Indicates that one entity serves as the main or first point of intake, reception, or admission for another entity.
-
B.
ageRange
chosen
Indicates the span of ages within which an entity or relationship is considered valid or applicable.
-
C.
portraysAgeGroup
Indicates that one entity depicts or represents another entity as belonging to a particular age group.
-
D.
children
Indicates that one entity is the offspring or direct descendant of another entity.
-
E.
primaryUserGroup
Indicates the main or default user group to which a user is primarily assigned or associated.
- 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_69a4936cb7448190914f5fe4b8d81607 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a79a3bbc81908d818c50a366b0f8 |
completed | March 1, 2026, 8:54 p.m. |
| PD | Predicate disambiguation | batch_69a4a510f61881909175d6d8719246cd |
completed | March 1, 2026, 8:44 p.m. |
Created at: March 1, 2026, 7:38 p.m.