Triple
T25784371
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Victoria Kipps |
E649379
|
entity |
| Predicate | hasEducationContext |
P155861
|
FINISHED |
| Object | elite academic environment |
—
|
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: elite academic environment | Statement: [Victoria Kipps, hasEducationContext, elite academic environment]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEducationContext Context triple: [Victoria Kipps, hasEducationContext, elite academic environment]
-
A.
hasEducationIn
Indicates that an entity has received education, training, or formal study in a specified field, subject, or discipline.
-
B.
hasEducationCharacteristic
chosen
Indicates that an entity possesses a specific educational attribute, quality, or feature (such as level, type, or status of education).
-
C.
hasEducationalStatus
Indicates that an entity possesses a particular level, state, or condition of formal education or academic attainment.
-
D.
hasEducationalProfile
Indicates that an entity is associated with a specific educational profile, detailing its education-related characteristics, qualifications, or academic background.
-
E.
hasEducationRight
Indicates that an entity possesses a legal or moral entitlement to receive education.
- 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_69e7ab33e9308190afe415dc6f9e8876 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f6562fd3488190be1acd8c526a28d2 |
completed | May 2, 2026, 7:53 p.m. |
| PD | Predicate disambiguation | batch_69f651a731508190bb0c8c2462eba224 |
completed | May 2, 2026, 7:33 p.m. |
Created at: April 22, 2026, 5:53 a.m.