Triple
T20547656
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NEET-PG |
E504512
|
entity |
| Predicate | syllabusBasedOn |
P112321
|
FINISHED |
| Object | MBBS curriculum prescribed in India |
—
|
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: MBBS curriculum prescribed in India | Statement: [NEET-PG, syllabusBasedOn, MBBS curriculum prescribed in India]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: syllabusBasedOn Context triple: [NEET-PG, syllabusBasedOn, MBBS curriculum prescribed in India]
-
A.
hasSyllabus
Indicates that an entity is associated with or includes a specific syllabus as part of its definition or content.
-
B.
hasCommonSyllabus
Indicates that two or more educational offerings share the same or substantially overlapping syllabus content.
-
C.
hasCurriculumBasis
chosen
Indicates that one entity’s curriculum is founded on, derived from, or guided by another entity as its basis.
-
D.
courseStructure
Indicates how a course is organized into its constituent parts, such as modules, units, lessons, and their sequencing or hierarchy.
-
E.
coursePar
Indicates that two entities (such as paths, lines, or trajectories) run alongside each other in the same general direction without intersecting.
- 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_69e0b4b52c048190952b4d0f430813a3 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6a2991ac8819089b8c2d70eb88952 |
completed | April 20, 2026, 10:03 p.m. |
| PD | Predicate disambiguation | batch_69e59fe5592c8190bb6122b784496d02 |
completed | April 20, 2026, 3:39 a.m. |
Created at: April 16, 2026, 11:38 a.m.