Triple
T4034810
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | No Child Left Behind Act |
E83802
|
entity |
| Predicate | introducedStandardizedTesting |
P53576
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [No Child Left Behind Act, introducedStandardizedTesting, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: introducedStandardizedTesting Context triple: [No Child Left Behind Act, introducedStandardizedTesting, true]
-
A.
standardizedAssessment
Indicates that an entity is evaluated using a uniform, systematically designed assessment administered and scored in a consistent manner across all subjects or contexts.
-
B.
firstStandardized
Indicates that an entity is the earliest or primary instance to which a standard or uniform specification has been first applied among comparable entities.
-
C.
introducedEducationSystem
Indicates that an entity established or brought a particular education system into use for another entity or context.
-
D.
laterStandardization
Indicates that one entity becomes standardized or formally established at a later time than another entity.
-
E.
standardizedSince
Indicates that something has been formally standardized starting from a specific point in time.
- 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_69aed92f7cf0819098e0539bdcc3767f |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefb11d92481909aaebbc250ff45b9 |
completed | March 9, 2026, 4:53 p.m. |
| PD | Predicate disambiguation | batch_69aef8fe440c819093a7fa22c4ff3f1a |
completed | March 9, 2026, 4:44 p.m. |
| PDg | Predicate description generation | batch_69aefa815f2c8190818c9ffd9d1bf478 |
completed | March 9, 2026, 4:51 p.m. |
Created at: March 9, 2026, 3:36 p.m.