Triple
T36224603
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North Omaha |
E1047946
|
entity |
| Predicate | hasEducationIssue |
P148777
|
FINISHED |
| Object | educational inequality |
—
|
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: educational inequality | Statement: [North Omaha, hasEducationIssue, educational inequality]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEducationIssue Context triple: [North Omaha, hasEducationIssue, educational inequality]
-
A.
hasEducationIssues
chosen
Indicates that an entity experiences problems, challenges, or deficiencies related to its education or educational process.
-
B.
educationLevelAtIssue
Indicates that the relationship concerns the specific level of education being questioned, disputed, or otherwise central to a particular issue or context.
-
C.
hasEducationIn
Indicates that an entity has received education, training, or formal study in a specified field, subject, or discipline.
-
D.
hasEducationCharacteristic
Indicates that an entity possesses a specific educational attribute, quality, or feature (such as level, type, or status of education).
-
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_69f76e42c878819095c8d19c0267fb87 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7b583a72481908411abb0daeb9f2d |
completed | May 3, 2026, 8:52 p.m. |
| PD | Predicate disambiguation | batch_69f7b4c44390819084fb5558b354658f |
completed | May 3, 2026, 8:49 p.m. |
Created at: May 3, 2026, 4:09 p.m.