Triple
T15911819
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | We the People: The Story of Our Constitution |
E385865
|
entity |
| Predicate | intendedLearningOutcome |
P12786
|
FINISHED |
| Object | understanding of how the Constitution was written |
—
|
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: understanding of how the Constitution was written | Statement: [We the People: The Story of Our Constitution, intendedLearningOutcome, understanding of how the Constitution was written]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: intendedLearningOutcome Context triple: [We the People: The Story of Our Constitution, intendedLearningOutcome, understanding of how the Constitution was written]
-
A.
educationalObjective
chosen
Indicates the intended learning goal, skill, or competency that an educational resource, activity, or program is designed to achieve.
-
B.
coreGoalTaught
Indicates that a fundamental or primary goal is explicitly taught or conveyed to someone.
-
C.
programOutcome
Indicates the resulting state, effect, or consequence produced by executing or completing a program.
-
D.
intendsTo
Indicates that one entity has the purpose, plan, or desire to perform an action involving another entity or outcome.
-
E.
structureLearning
Indicates a process in which an agent infers or constructs the underlying structure or dependency relationships within a set of variables, data, or a model.
- 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_69d86da686e4819097cbf3b1fc2d881d |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e17d4d08f481909f38b75e3f42d9ab |
completed | April 17, 2026, 12:22 a.m. |
| PD | Predicate disambiguation | batch_69e142ca3b208190946c3aa4c1e6087c |
completed | April 16, 2026, 8:12 p.m. |
Created at: April 10, 2026, 4:52 a.m.