Triple
T37628674
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hewitt School |
E936279
|
entity |
| Predicate | targetStudentGender |
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: [Hewitt School, targetStudentGender, girls]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetStudentGender Context triple: [Hewitt School, targetStudentGender, girls]
-
A.
targetStudentGroup
Indicates a relationship where something is directed, tailored, or intended specifically for a particular group of students.
-
B.
hasPupilsGender
chosen
Indicates that an entity has pupils whose gender is specified or characterized in some way.
-
C.
targetStudentsFrom
Indicates that an entity directs its efforts, services, or offerings specifically toward a defined group of students.
-
D.
targetStudentService
Indicates a relationship where a particular student is the intended recipient or focus of a specific service or support action.
-
E.
admissionGender
Indicates the gender-based criteria or classification applied in the context of admission or entry decisions.
- 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_69f76ed24820819081bafd36e9088701 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69ff3b32ee148190a3ba3b7600943fef |
completed | May 9, 2026, 1:48 p.m. |
| PD | Predicate disambiguation | batch_69ff3a238af88190a2c2245e30299e48 |
completed | May 9, 2026, 1:44 p.m. |
Created at: May 3, 2026, 4:18 p.m.