Triple
T13430038
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nyingma school |
E313581
|
entity |
| Predicate | hasLayComponent |
P109893
|
FINISHED |
| Object | lay practitioners |
—
|
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: lay practitioners | Statement: [Nyingma school, hasLayComponent, lay practitioners]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLayComponent Context triple: [Nyingma school, hasLayComponent, lay practitioners]
-
A.
hasLayBody
Indicates that an entity possesses or is associated with a lay (non-clerical or non-professional) governing or decision-making body.
-
B.
hasLayOrder
Indicates that one entity has issued, received, or is subject to a formal lay order associated with another entity.
-
C.
hasLayoutElement
Indicates that one entity includes, contains, or is associated with a specific layout element as part of its structural or visual arrangement.
-
D.
hasLayMembersCount
Indicates the number of lay (non-clergy or non-professional) members associated with an entity.
-
E.
hasLayout
Indicates that one entity defines or is associated with the structural arrangement or organization (layout) of another 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_69d806ad0c44819088833ae1ec9e9690 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaed304ac8190a8021f749de8164c |
completed | April 12, 2026, 2:40 p.m. |
| PD | Predicate disambiguation | batch_69d9a03926188190ab3948d1f5d3941f |
completed | April 11, 2026, 1:13 a.m. |
| PDg | Predicate description generation | batch_69dadcce5a808190847f2a7833b67a5a |
completed | April 11, 2026, 11:44 p.m. |
Created at: April 9, 2026, 9:40 p.m.