Triple
T4040910
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lady Margaret Hall, Oxford |
E83944
|
entity |
| Predicate | genderPolicyChange |
P9880
|
FINISHED |
| Object | became coeducational in 1979 |
—
|
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: became coeducational in 1979 | Statement: [Lady Margaret Hall, Oxford, genderPolicyChange, became coeducational in 1979]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genderPolicyChange Context triple: [Lady Margaret Hall, Oxford, genderPolicyChange, became coeducational in 1979]
-
A.
hasGenderPolicy
Indicates that an entity has adopted, implemented, or is governed by a specific policy related to gender issues or gender equality.
-
B.
genderEquality
Indicates that the relationship or action promotes, reflects, or ensures equal rights, opportunities, and treatment for all genders without discrimination.
-
C.
policyShift
chosen
Indicates a change or adjustment in an existing policy, typically reflecting a new direction, priority, or approach.
-
D.
stanceOnGenderIssues
Indicates a person or entity’s views, attitudes, or position regarding gender-related topics, policies, or inequalities.
-
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_69aed92f7cf0819098e0539bdcc3767f |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefb3a9314819095dcf47675eedb48 |
completed | March 9, 2026, 4:54 p.m. |
| PD | Predicate disambiguation | batch_69aef900386481909d04555a9ec9b0e3 |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:37 p.m.