Triple
T35371139
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Royal Masonic School for Girls |
E1021771
|
entity |
| Predicate | educatesGender |
P183070
|
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: [Royal Masonic School for Girls, educatesGender, girls]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: educatesGender Context triple: [Royal Masonic School for Girls, educatesGender, girls]
-
A.
educates
Indicates that one entity provides instruction, knowledge, or training to another entity.
-
B.
governsGender
Indicates that one entity determines or constrains the gender classification or gender-related properties of another entity.
-
C.
genderEquality
Indicates that the relationship or action promotes, reflects, or ensures equal rights, opportunities, and treatment for all genders without discrimination.
-
D.
genderCategories
Indicates the classification of an entity into one or more gender-related categories or identities.
-
E.
sexDifference
Indicates a relationship where two entities differ from each other specifically in terms of biological sex.
- F. None of above. chosen
Provenance (4 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_69f76df000488190ab7c97f565677055 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f795b5228c8190adb5bf86e581f70c |
completed | May 3, 2026, 6:36 p.m. |
| PD | Predicate disambiguation | batch_69f79104f5b48190a496cdffde8472da |
completed | May 3, 2026, 6:16 p.m. |
| PDg | Predicate description generation | batch_69f79527c7bc8190a69d87bec01f65c8 |
completed | May 3, 2026, 6:34 p.m. |
Created at: May 3, 2026, 4:03 p.m.