Triple
T179469
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Janet–Cartan theorem |
E3651
|
entity |
| Predicate | mathematicalSubjectClassification |
P7033
|
FINISHED |
| Object | 53C21 |
—
|
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: 53C21 | Statement: [Janet–Cartan theorem, mathematicalSubjectClassification, 53C21]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mathematicalSubjectClassification Context triple: [Janet–Cartan theorem, mathematicalSubjectClassification, 53C21]
-
A.
mathematicallyUses
Indicates that one entity employs or applies another entity within a mathematical context, such as in a formula, proof, computation, or theoretical framework.
-
B.
libraryOfCongressClassification
Indicates that one entity is assigned a Library of Congress Classification code that organizes it within the Library of Congress subject-based cataloging system.
-
C.
mathematicalFormalizationYear
Indicates the year in which something was first formally defined or expressed in mathematical terms.
-
D.
deweyDecimalClassification
Indicates the Dewey Decimal System classification assigned to an item, expressing its subject-based placement within a library’s organizational scheme.
-
E.
subjectMatter
Indicates the topic, theme, or content area that something (such as a work, document, or discussion) is about.
- 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_69a25374990081909766d30c79a18e0e |
completed | Feb. 28, 2026, 2:31 a.m. |
| NER | Named-entity recognition | batch_69a25900709c8190a65e778936be5dd5 |
completed | Feb. 28, 2026, 2:54 a.m. |
| PD | Predicate disambiguation | batch_69a2566b53d481909c0ed40dd3719e8c |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a2582b7f648190b0ef676b8bdc1c65 |
completed | Feb. 28, 2026, 2:51 a.m. |
Created at: Feb. 28, 2026, 2:39 a.m.