Triple
T21997520
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CSAT (General Studies Paper II) |
E543243
|
entity |
| Predicate | marksCountedForMerit |
P135589
|
FINISHED |
| Object | no |
—
|
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: no | Statement: [CSAT (General Studies Paper II), marksCountedForMerit, no]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: marksCountedForMerit Context triple: [CSAT (General Studies Paper II), marksCountedForMerit, no]
-
A.
areCountedBy
Indicates that one entity serves as the counting mechanism, record, or process by which the quantity of another entity is determined.
-
B.
isCountedAs
chosen
Indicates that one entity is treated or included as part of the tally, total, or quantitative assessment of another entity.
-
C.
gradeCount
Indicates the number of grades associated with a given entity or context.
-
D.
hasGradeCount
Indicates a relationship where an entity is associated with the number of grades it has or has received.
-
E.
majorHonourCount
Indicates the number of significant or top-level honors or awards associated with an entity.
- 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_69e11e2c814c8190837d072789000486 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f1276774508190b96870266e10979a |
completed | April 28, 2026, 9:32 p.m. |
| PD | Predicate disambiguation | batch_69e6f62dc9d88190ae387f145f9528de |
completed | April 21, 2026, 3:59 a.m. |
Created at: April 16, 2026, 8:19 p.m.