Triple
T26949891
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Haeinsa |
E678751
|
entity |
| Predicate | TripitakaKoreanaNumberOfBlocks |
P162011
|
FINISHED |
| Object | over 81000 |
—
|
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: over 81000 | Statement: [Haeinsa, TripitakaKoreanaNumberOfBlocks, over 81000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: TripitakaKoreanaNumberOfBlocks Context triple: [Haeinsa, TripitakaKoreanaNumberOfBlocks, over 81000]
-
A.
TripitakaKoreanaLanguage
Indicates that the Tripitaka Koreana is written or recorded in a particular language.
-
B.
numberOfSutras
Indicates the quantity or count of sutras associated with a given entity.
-
C.
hasNumberOfKandas
Indicates the relationship specifying how many kandas (sections or books) are associated with a given entity.
-
D.
numberOfTractates
Indicates the total count of tractates associated with a given entity or collection.
-
E.
hasNumberOfKoans
Indicates the relationship that specifies how many koans are associated with or contained by a given entity.
- 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_69eeeb4e75f08190b14fc91ca4a91488 |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f622abdfac8190988421c946411d7e |
completed | May 2, 2026, 4:13 p.m. |
| PD | Predicate disambiguation | batch_69f620e0b37481909a280574decbd443 |
completed | May 2, 2026, 4:05 p.m. |
| PDg | Predicate description generation | batch_69f621c7d3e0819095b1f327637ae4f9 |
completed | May 2, 2026, 4:09 p.m. |
Created at: April 27, 2026, 6:24 a.m.