Triple
T21550369
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bachelor of Science in Mathematics |
E531743
|
entity |
| Predicate | typicalCoreTopic |
P43765
|
FINISHED |
| Object | calculus |
—
|
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: calculus | Statement: [Bachelor of Science in Mathematics, typicalCoreTopic, calculus]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalCoreTopic Context triple: [Bachelor of Science in Mathematics, typicalCoreTopic, calculus]
-
A.
typicalCourseTopic
chosen
Indicates that a given topic is commonly or characteristically covered as part of a particular course.
-
B.
coveredTopics
Indicates that certain subjects or themes have been addressed or included within a discussion, document, or activity.
-
C.
typicalCoreType
Indicates that something is a standard or characteristic core type within a given classification or system.
-
D.
primaryTopicOf
Indicates that a given subject is the main or central topic described by another resource (such as a document, page, or record).
-
E.
featuresTopic
Indicates that something (such as a work, event, or item) prominently includes, focuses on, or is organized around a particular topic.
- 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_69e0c460232c81908de2c3819d17c00e |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69eeb59258b88190966c18f1f519dad6 |
completed | April 27, 2026, 1:02 a.m. |
| PD | Predicate disambiguation | batch_69e6320766308190ba5dca2f7c826aa4 |
completed | April 20, 2026, 2:02 p.m. |
Created at: April 16, 2026, 6:28 p.m.