Triple
T16287148
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jeff Davis County, Georgia |
E395416
|
entity |
| Predicate | publicEducationLevel |
P97458
|
FINISHED |
| Object | K-12 |
—
|
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: K-12 | Statement: [Jeff Davis County, Georgia, publicEducationLevel, K-12]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: publicEducationLevel Context triple: [Jeff Davis County, Georgia, publicEducationLevel, K-12]
-
A.
educationStatus
Indicates the current or achieved level, stage, or condition of an entity’s formal education.
-
B.
governsLevelOfEducation
Indicates that one entity has authority or control over determining the level or standard of education provided to another entity.
-
C.
educationLevelCharacteristic
Indicates that one entity specifies, describes, or constrains the education level associated with another entity.
-
D.
educationType
Indicates the specific category or level of education associated with an entity, such as formal, informal, primary, secondary, or higher education.
-
E.
educationLevelsCovered
chosen
Indicates the range or specific levels of education that are included or addressed by something (such as a program, policy, or resource).
- 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_69d87f22c7248190a54c949738441e2e |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e24915a5948190a11b8e83b7974dda |
completed | April 17, 2026, 2:52 p.m. |
| PD | Predicate disambiguation | batch_69e219f68d308190b71c1601303f0628 |
completed | April 17, 2026, 11:31 a.m. |
Created at: April 10, 2026, 5:05 a.m.