Triple
T1157566
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PSAT/NMSQT |
E24416
|
entity |
| Predicate | evidenceBasedReadingAndWritingScoreRange |
P23740
|
FINISHED |
| Object | 160–760 |
—
|
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: 160–760 | Statement: [PSAT/NMSQT, evidenceBasedReadingAndWritingScoreRange, 160–760]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: evidenceBasedReadingAndWritingScoreRange Context triple: [PSAT/NMSQT, evidenceBasedReadingAndWritingScoreRange, 160–760]
-
A.
readingAndWritingSectionScoreRange
chosen
Indicates the range of possible or achieved scores associated with the reading and writing section of an assessment.
-
B.
scoreScaleVerbal
Indicates the verbal description or label corresponding to a particular score or score range on a scale.
-
C.
scoreScaleAnalyticalWriting
Indicates the scoring scale or range used to evaluate and rate analytical writing performance.
-
D.
intendedReadingLevel
Indicates the reading proficiency or audience level that a text or resource is designed or meant to be understood by.
-
E.
scoreIncrementAnalyticalWriting
Indicates an increase in a subject’s score specifically attributable to their analytical writing performance or improvement.
- 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_69a494060e148190abb42f971242c197 |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bcab3cd08190ad06ea007042a8fc |
completed | March 1, 2026, 10:24 p.m. |
| PD | Predicate disambiguation | batch_69a4bb50d19c81908a98dbbb04a8906f |
completed | March 1, 2026, 10:18 p.m. |
Created at: March 1, 2026, 7:44 p.m.