Triple
T38660856
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | bhikkhunī order |
E940328
|
entity |
| Predicate | hasRuleCount |
P85168
|
FINISHED |
| Object | more rules than bhikkhu order |
—
|
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: more rules than bhikkhu order | Statement: [bhikkhunī order, hasRuleCount, more rules than bhikkhu order]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRuleCount Context triple: [bhikkhunī order, hasRuleCount, more rules than bhikkhu order]
-
A.
hasNumberOfRules
chosen
Indicates the specific count of rules associated with or applicable to an entity.
-
B.
hasRule
Indicates that an entity is governed, constrained, or defined by a specific rule or set of rules.
-
C.
hasRuleFor
Indicates that one entity defines or applies a rule that governs or constrains another entity or situation.
-
D.
hasRuleOver
Indicates that one entity holds authority, control, or governance over another entity.
-
E.
numberOfRulesPlanned
Indicates the planned or intended count of rules associated with an entity or process.
- 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_69f76edfde348190bf6529d9f49ecd62 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fcdfbc71c481908ba7f87907b17782 |
completed | May 7, 2026, 6:53 p.m. |
| PD | Predicate disambiguation | batch_69fcdbe580b8819087f143596b2c79c0 |
completed | May 7, 2026, 6:37 p.m. |
Created at: May 3, 2026, 4:33 p.m.