Triple
T31779415
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Glenelg, Maryland |
E811155
|
entity |
| Predicate | hasSchoolQuality |
P157187
|
FINISHED |
| Object | high-performing public schools |
—
|
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: high-performing public schools | Statement: [Glenelg, Maryland, hasSchoolQuality, high-performing public schools]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSchoolQuality Context triple: [Glenelg, Maryland, hasSchoolQuality, high-performing public schools]
-
A.
hasPublicSchoolQuality
chosen
Indicates that an entity is associated with a certain level or rating of public school quality.
-
B.
educationQualityComparableTo
Indicates that the quality of education provided by one entity is similar or equivalent to that provided by another entity.
-
C.
hasSchool
Indicates that an entity possesses, is associated with, or is served by a particular school.
-
D.
hasSchoolIn
Indicates that a school is located within or operates in a specified place or region.
-
E.
hasSchoolsAccess
Indicates that one entity has permission or the ability to access schools or school-related resources associated with 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_69f348e544a48190ab6e700b05f6438c |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69fb563aec448190875410fb1a3ed624 |
completed | May 6, 2026, 2:54 p.m. |
| PD | Predicate disambiguation | batch_69fb35b9ede881908aaae93a215525df |
completed | May 6, 2026, 12:36 p.m. |
Created at: April 30, 2026, 11:36 p.m.