Triple
T15210947
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NCAA Division I |
E363510
|
entity |
| Predicate | hasNumberOfMemberSchools |
P276
|
FINISHED |
| Object | over 350 |
—
|
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: over 350 | Statement: [NCAA Division I, hasNumberOfMemberSchools, over 350]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfMemberSchools Context triple: [NCAA Division I, hasNumberOfMemberSchools, over 350]
-
A.
hasNumberOfSchools
Indicates the quantity of schools associated with a given entity.
-
B.
hasNumberOfMemberInstitutions
chosen
Indicates the quantitative count of member institutions associated with a given entity.
-
C.
hasAffiliatedSchoolsIn
Indicates that an entity maintains formal affiliations or partnerships with schools located in a specified place or region.
-
D.
hasMultipleCampuses
Indicates that an educational institution operates more than one physical campus location.
-
E.
hasAffiliatedCollegesIn
Indicates that an institution maintains affiliated colleges located within a specified geographic area or jurisdiction.
- 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_69d85a0b78bc8190b6e5ad51a2c4cfc5 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0076ad4ec81908d36f541fca08d72 |
completed | April 15, 2026, 9:47 p.m. |
| PD | Predicate disambiguation | batch_69deb97ee9d881908711dbe12a55283c |
completed | April 14, 2026, 10:02 p.m. |
Created at: April 10, 2026, 3:11 a.m.