Triple
T27710741
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Loyola Elementary School |
E698669
|
entity |
| Predicate | hasStudentAgeRangeFrom |
P72504
|
FINISHED |
| Object | approximately 5 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 5 years | Statement: [Loyola Elementary School, hasStudentAgeRangeFrom, approximately 5 years]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStudentAgeRangeFrom Context triple: [Loyola Elementary School, hasStudentAgeRangeFrom, approximately 5 years]
-
A.
hasDegreeRange
Indicates that an entity is associated with a minimum and maximum degree value defining a range.
-
B.
hasGradeSpan
Indicates the range of grade levels or educational stages that an entity (such as a school or program) covers or serves.
-
C.
hasEnrollmentRange
Indicates that there is a specified minimum and/or maximum number of participants allowed or expected for an enrollment in a given context.
-
D.
hasApproximateAgeRange
Indicates that one entity is associated with another entity representing an estimated or non-exact span of ages.
-
E.
acceptsPupilsFromAge
chosen
Indicates that an entity (such as a school or program) enrolls or admits pupils starting from a specified minimum age.
- 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_69fbbc49da8c8190902bbb05d2477cab |
completed | May 6, 2026, 10:10 p.m. |
| PD | Predicate disambiguation | batch_69fbb13f34b08190bbbb220ac1e6e666 |
completed | May 6, 2026, 9:23 p.m. |
Created at: April 27, 2026, 3:02 p.m.