Triple
T37733506
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Second Buddhist Council |
E940220
|
entity |
| Predicate | numberOfIssuesDiscussed |
P31088
|
FINISHED |
| Object | ten points of discipline |
—
|
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: ten points of discipline | Statement: [Second Buddhist Council, numberOfIssuesDiscussed, ten points of discipline]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfIssuesDiscussed Context triple: [Second Buddhist Council, numberOfIssuesDiscussed, ten points of discipline]
-
A.
numberOfIssues
chosen
Indicates the quantity of issues associated with a given entity or context.
-
B.
numberOfProblems
Indicates the quantity or count of problems associated with a given entity or situation.
-
C.
issueNumber
Indicates the specific numeric identifier assigned to distinguish one issue from others within a series or collection.
-
D.
numberOfDialogues
Indicates the total count of dialogues associated with or occurring between the referenced entities.
-
E.
involvesIssue
Indicates that an action, event, or entity is related to, concerns, or includes a particular issue.
- 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_69f76edefd048190a32212c5c3919531 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037c8efcd4819088c2aeead65d93df |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a1772e48190ba738c6d11b321e2 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:18 p.m.