Triple
T6562170
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Learning and Labor |
E153809
|
entity |
| Predicate | reflectsEmphasisOn |
P17414
|
FINISHED |
| Object | rigorous academic study |
—
|
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: rigorous academic study | Statement: [Learning and Labor, reflectsEmphasisOn, rigorous academic study]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reflectsEmphasisOn Context triple: [Learning and Labor, reflectsEmphasisOn, rigorous academic study]
-
A.
hasEmphasis
chosen
Indicates that one element is given special stress, importance, or prominence relative to others.
-
B.
positionEmphasized
Indicates that a particular position, stance, or role is given special prominence or stress relative to others.
-
C.
reflects
Indicates that one entity (often a surface, medium, or representation) throws back, mirrors, or otherwise shows an image, property, or state of another entity.
-
D.
focusesOn
Indicates that one entity directs its attention, effort, or primary activity toward another entity or specific subject.
-
E.
designEmphasizes
Indicates that a design intentionally places special importance or focus on a particular feature, principle, or aspect over others.
- 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_69c6880cb35881909b763eb0125236b9 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6c1b15d3481908ae66e3d7564b352 |
completed | March 27, 2026, 5:43 p.m. |
| PD | Predicate disambiguation | batch_69c6acf6d4148190914b19e9affd8c76 |
completed | March 27, 2026, 4:14 p.m. |
Created at: March 27, 2026, 1:52 p.m.