Triple
T27710742
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Loyola Elementary School |
E698669
|
entity |
| Predicate | hasStudentAgeRangeTo |
P122542
|
FINISHED |
| Object | approximately 12 years |
—
|
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: approximately 12 years | Statement: [Loyola Elementary School, hasStudentAgeRangeTo, approximately 12 years]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStudentAgeRangeTo Context triple: [Loyola Elementary School, hasStudentAgeRangeTo, approximately 12 years]
-
A.
hasDegreeRange
Indicates that an entity is associated with a minimum and maximum degree value defining a range.
-
B.
hasEnrollmentRange
Indicates that there is a specified minimum and/or maximum number of participants allowed or expected for an enrollment in a given context.
-
C.
hasGradeSpan
Indicates the range of grade levels or educational stages that an entity (such as a school or program) covers or serves.
-
D.
hasApproximateAgeRange
chosen
Indicates that one entity is associated with another entity representing an estimated or non-exact span of ages.
-
E.
containsAge
Indicates that one entity includes or specifies the age value or age-related information of another entity.
- 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_69ef590f655c81909f93893b3b3219b2 |
completed | April 27, 2026, 12:39 p.m. |
| NER | Named-entity recognition | batch_69fbc36ce1f88190a7fa1656b714e107 |
completed | May 6, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69fbbd13595c81908719f52c3d37a7e8 |
completed | May 6, 2026, 10:13 p.m. |
Created at: April 27, 2026, 3:02 p.m.