Triple
T27004100
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IGCSE |
E680192
|
entity |
| Predicate | subjectStructure |
P170640
|
FINISHED |
| Object | offered as separate subject qualifications |
—
|
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: offered as separate subject qualifications | Statement: [IGCSE, subjectStructure, offered as separate subject qualifications]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: subjectStructure Context triple: [IGCSE, subjectStructure, offered as separate subject qualifications]
-
A.
majorStructure
Indicates that one entity functions as a primary or principal structural component or framework in relation to another entity.
-
B.
questionStructure
Indicates the structural or grammatical arrangement that defines how a question is formed or organized.
-
C.
courseStructure
Indicates how a course is organized into its constituent parts, such as modules, units, lessons, and their sequencing or hierarchy.
-
D.
subjectType
Indicates the classification or category that defines what kind of entity the subject is.
-
E.
academicStructure
Indicates a hierarchical or organizational relationship within an academic system, such as how programs, departments, courses, or degrees are structured and related to one another.
- 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_69eeeb52908c8190bd246244686aa455 |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f693ffa7908190aa4c451b16df9be6 |
completed | May 3, 2026, 12:17 a.m. |
| PD | Predicate disambiguation | batch_69f690eb1e948190aab41a89969519a5 |
completed | May 3, 2026, 12:03 a.m. |
| PDg | Predicate description generation | batch_69f6938244648190a553b532387b812c |
completed | May 3, 2026, 12:14 a.m. |
Created at: April 27, 2026, 6:59 a.m.