Triple
T21331970
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cheltenham College |
E525927
|
entity |
| Predicate | previousGenderPolicy |
P277
|
FINISHED |
| Object | boys only |
—
|
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: boys only | Statement: [Cheltenham College, previousGenderPolicy, boys only]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: previousGenderPolicy Context triple: [Cheltenham College, previousGenderPolicy, boys only]
-
A.
hasGenderPolicy
chosen
Indicates that an entity has adopted, implemented, or is governed by a specific policy related to gender issues or gender equality.
-
B.
demographicPolicy
Indicates a relationship where an authority or organization establishes or applies rules and measures intended to influence the size, structure, or composition of a population.
-
C.
hasGenderHistory
Indicates that an entity has undergone or experienced a change or transition in gender over time.
-
D.
governsGender
Indicates that one entity determines or constrains the gender classification or gender-related properties of another entity.
-
E.
hasGenderPractice
Indicates a relationship where an entity engages in, follows, or applies a particular gender-related practice, norm, or behavior.
- 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_69e0b51b90788190a4dd823d962626da |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7ab54706081909445f9cd91a43788 |
completed | April 21, 2026, 4:52 p.m. |
| PD | Predicate disambiguation | batch_69e6161feea4819091d13bb003363279 |
completed | April 20, 2026, 12:03 p.m. |
Created at: April 16, 2026, 4:42 p.m.