Triple
T4552258
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Divergent Series |
E120391
|
entity |
| Predicate | hasMathematicalSubjectClassification |
P7033
|
FINISHED |
| Object | 40A05 |
—
|
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: 40A05 | Statement: [Divergent Series, hasMathematicalSubjectClassification, 40A05]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMathematicalSubjectClassification Context triple: [Divergent Series, hasMathematicalSubjectClassification, 40A05]
-
A.
mathematicalSubjectClassification
chosen
Indicates that one entity classifies the mathematical subject area or field to which another entity (such as a work, concept, or topic) belongs.
-
B.
isClassifiedUnder
Indicates that one entity is categorized or grouped within a broader class, type, or category represented by another entity.
-
C.
hasSubdiscipline
Indicates that one discipline includes another, more specialized field of study as a subordinate branch.
-
D.
hasSubjectOfStudy
Indicates that an entity (such as a person or organization) focuses on, researches, or specializes in a particular field or topic of study.
-
E.
hasBibliographicCategory
Indicates that an entity is associated with a specific bibliographic classification or category within a cataloging or documentation system.
- 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_69bd4636f1648190a701445c2fcd9c17 |
completed | March 20, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69bd57f7b9748190af29d02fc77b02e0 |
completed | March 20, 2026, 2:21 p.m. |
| PD | Predicate disambiguation | batch_69bd5223423c81908317351b58cff5f5 |
completed | March 20, 2026, 1:56 p.m. |
Created at: March 20, 2026, 1:09 p.m.