Triple
T25707972
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alma Pudden |
E644646
|
entity |
| Predicate | schoolGenderType |
P90562
|
FINISHED |
| Object | girls’ school |
—
|
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’ school | Statement: [Alma Pudden, schoolGenderType, girls’ school]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: schoolGenderType Context triple: [Alma Pudden, schoolGenderType, girls’ school]
-
A.
hasCoeducation
Indicates that an educational institution includes both male and female students together in its instructional programs.
-
B.
hasPupilsGender
chosen
Indicates that an entity has pupils whose gender is specified or characterized in some way.
-
C.
admissionGender
Indicates the gender-based criteria or classification applied in the context of admission or entry decisions.
-
D.
schoolSystemType
Indicates the classification or organizational model of a school system (e.g., public, private, charter, or other structural type).
-
E.
governsGender
Indicates that one entity determines or constrains the gender classification or gender-related properties 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_69e77e83c8ec8190bf52fcdac4838984 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f61f12b0f08190bc4a16907941864c |
completed | May 2, 2026, 3:58 p.m. |
| PD | Predicate disambiguation | batch_69f61b37a5648190b10d33ae205ccfee |
completed | May 2, 2026, 3:41 p.m. |
Created at: April 21, 2026, 9:06 p.m.