Triple
T12778502
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amitāyurdhyāna Sūtra |
E305439
|
entity |
| Predicate | teachesNumberOfContemplations |
P106857
|
FINISHED |
| Object | 16 |
—
|
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: 16 | Statement: [Amitāyurdhyāna Sūtra, teachesNumberOfContemplations, 16]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: teachesNumberOfContemplations Context triple: [Amitāyurdhyāna Sūtra, teachesNumberOfContemplations, 16]
-
A.
hasNumberOfKoans
Indicates the relationship that specifies how many koans are associated with or contained by a given entity.
-
B.
numberOfLectures
Indicates the total count of lectures associated with a given entity or context.
-
C.
hasNumberOfLessons
Indicates the specific count of lessons associated with an entity.
-
D.
hasNumberOfDoctrines
Indicates the relationship that specifies how many doctrines are associated with a given entity.
-
E.
numberOfKoans
Indicates the quantity or count of koans associated with a given entity or context.
- 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_69d7bdf2b43c819098ae5aa68e61ea58 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96e595e008190b42dff3012d17d66 |
completed | April 10, 2026, 9:40 p.m. |
| PD | Predicate disambiguation | batch_69d9640ba0688190973e4e7ec8d4a8e0 |
completed | April 10, 2026, 8:56 p.m. |
| PDg | Predicate description generation | batch_69d96d87078c819083ea724238992204 |
completed | April 10, 2026, 9:37 p.m. |
Created at: April 9, 2026, 5:29 p.m.