Triple
T19160395
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Standards of Learning tests |
E469036
|
entity |
| Predicate | testWindow |
P134672
|
FINISHED |
| Object | spring testing period |
—
|
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: spring testing period | Statement: [Standards of Learning tests, testWindow, spring testing period]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: testWindow Context triple: [Standards of Learning tests, testWindow, spring testing period]
-
A.
windowType
Indicates the specific kind or category of window associated with an entity.
-
B.
windowArea
Indicates the total surface area occupied by a window (or windows) in a given context.
-
C.
test
Indicates that an entity performs, undergoes, or is associated with a testing or examination process involving another entity or condition.
-
D.
typicalApplicationWindow
Indicates that something is a standard or commonly used application window in a software environment.
-
E.
windowManagement
Indicates the relationship or action of controlling, arranging, or interacting with on-screen windows within a graphical user interface.
- F. None of above. chosen
Provenance (4 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_69d8dd084ff48190ac0f8c46ee722629 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5eebc52dc819085666dbbeea365a6 |
completed | April 20, 2026, 9:15 a.m. |
| PD | Predicate disambiguation | batch_69e4b9b83d6881908e6271c620f74100 |
completed | April 19, 2026, 11:17 a.m. |
| PDg | Predicate description generation | batch_69e4bfe9ef7081908a74a57d1fc731ea |
completed | April 19, 2026, 11:43 a.m. |
Created at: April 10, 2026, 12:06 p.m.