Triple
T5296236
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shenango Township, Pennsylvania |
E119861
|
entity |
| Predicate | hasPublicEducationLevel |
P177
|
FINISHED |
| Object | elementary school |
—
|
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: elementary school | Statement: [Shenango Township, Pennsylvania, hasPublicEducationLevel, elementary school]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPublicEducationLevel Context triple: [Shenango Township, Pennsylvania, hasPublicEducationLevel, elementary school]
-
A.
educationStatus
Indicates the current or achieved level, stage, or condition of an entity’s formal education.
-
B.
educationType
chosen
Indicates the specific category or level of education associated with an entity, such as formal, informal, primary, secondary, or higher education.
-
C.
hasHigherEducationAccess
Indicates that one entity has access to higher education opportunities or institutions relative to another entity or context.
-
D.
educationLevelCharacteristic
Indicates that one entity specifies, describes, or constrains the education level associated with another entity.
-
E.
educatedAt
Indicates that an entity received education or formal training at a specified institution or place of learning.
- 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_69bd446f22b88190b6a47fb91c68a3e7 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd8682d18c8190bbb35cc75c8a7c12 |
completed | March 20, 2026, 5:40 p.m. |
| PD | Predicate disambiguation | batch_69bd844dfdac819086efedd1cbebff84 |
completed | March 20, 2026, 5:30 p.m. |
Created at: March 20, 2026, 1:53 p.m.