Triple
T2543296
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Transcendental Analytic |
E57836
|
entity |
| Predicate | keyQuestion |
P4939
|
FINISHED |
| Object | How are synthetic a priori judgments possible? |
—
|
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: How are synthetic a priori judgments possible? | Statement: [Transcendental Analytic, keyQuestion, How are synthetic a priori judgments possible?]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: keyQuestion Context triple: [Transcendental Analytic, keyQuestion, How are synthetic a priori judgments possible?]
-
A.
questionText
Indicates the textual content of a question as it is posed or displayed.
-
B.
centralQuestion
Indicates that something is the main issue, problem, or inquiry around which a discussion, work, or investigation is focused.
-
C.
questionType
Indicates the specific category or kind of question that an item, query, or prompt belongs to.
-
D.
questionForm
Indicates that one entity is expressed or structured in the form of a question directed toward another entity or context.
-
E.
hasKeyQuestion
chosen
Indicates that one entity possesses or is associated with a primary or central question relevant to another entity.
- 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_69ab4a5212d88190b989ce129f2ad87f |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd2bf6cac819083a9ab9d041d8641 |
completed | March 7, 2026, 7:24 a.m. |
| PD | Predicate disambiguation | batch_69abd0c63964819092d5f578195ae8dd |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:47 p.m.