Triple
T21436499
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Santa Catalina School |
E528825
|
entity |
| Predicate | hasUpperSchoolGender |
P90562
|
FINISHED |
| Object | girls |
—
|
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: girls | Statement: [Santa Catalina School, hasUpperSchoolGender, girls]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUpperSchoolGender Context triple: [Santa Catalina School, hasUpperSchoolGender, girls]
-
A.
hasUpperSchool
Indicates that an educational institution includes or is associated with an upper-level school (typically serving older or advanced students).
-
B.
hasCoeducation
Indicates that an educational institution includes both male and female students together in its instructional programs.
-
C.
hasPupilsGender
chosen
Indicates that an entity has pupils whose gender is specified or characterized in some way.
-
D.
hasGymnasium
Indicates that one entity possesses, includes, or is equipped with a gymnasium as a facility or feature.
-
E.
correspondsToMaleGrade
Indicates that one item or classification is associated with, or equivalent to, the grading scale or grade level used for males.
- 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_69e0c4569fa081908101baa24f8745db |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e8b537f39081909220577618657805 |
completed | April 22, 2026, 11:47 a.m. |
| PD | Predicate disambiguation | batch_69e61639ee288190889ffd500d1260f6 |
completed | April 20, 2026, 12:04 p.m. |
Created at: April 16, 2026, 6:03 p.m.