Triple
T19977547
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | State of Texas Assessments of Academic Readiness |
E493730
|
entity |
| Predicate | testingWindow |
P134672
|
FINISHED |
| Object | spring |
—
|
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 | Statement: [State of Texas Assessments of Academic Readiness, testingWindow, spring]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: testingWindow Context triple: [State of Texas Assessments of Academic Readiness, testingWindow, spring]
-
A.
testWindow
chosen
Indicates that an entity functions as, or is associated with, a specific window used for testing or experimental purposes.
-
B.
windowType
Indicates the specific kind or category of window associated with an entity.
-
C.
typicalApplicationWindow
Indicates that something is a standard or commonly used application window in a software environment.
-
D.
windowArea
Indicates the total surface area occupied by a window (or windows) in a given context.
-
E.
test
Indicates that an entity performs, undergoes, or is associated with a testing or examination process involving another entity or condition.
- 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_69da626a67648190af9653832a3aeced |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e65d1054e08190993b92b86ec5bbc8 |
completed | April 20, 2026, 5:06 p.m. |
| PD | Predicate disambiguation | batch_69e537fae79c81909eae39500766d0b6 |
completed | April 19, 2026, 8:15 p.m. |
Created at: April 11, 2026, 3:27 p.m.