Triple
T12262025
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Buddhist Lent |
E292246
|
entity |
| Predicate | layAspect |
P61123
|
FINISHED |
| Object | increased observance of precepts |
—
|
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: increased observance of precepts | Statement: [Buddhist Lent, layAspect, increased observance of precepts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: layAspect Context triple: [Buddhist Lent, layAspect, increased observance of precepts]
-
A.
onAspect
Indicates that one entity is positioned on a particular side, surface, or facet of another entity.
-
B.
lays
Indicates that one entity deposits or places something, typically eggs or objects, onto a surface or in a location.
-
C.
coversAspect
chosen
Indicates that one entity addresses, includes, or deals with a particular aspect or facet of another entity or topic.
-
D.
aspect
Indicates a specific temporal phase or manner in which an action, event, or state unfolds or is viewed (e.g., ongoing, completed, habitual).
-
E.
symbolicAspect
Indicates that one entity functions as a symbol or emblem that represents, expresses, or conveys a particular meaning, quality, or concept of another entity.
- 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_69d6ab6856488190b5d31178d5015f8e |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d9380a5e78819086bd4dfe9a83d1f5 |
completed | April 10, 2026, 5:48 p.m. |
| PD | Predicate disambiguation | batch_69d91c4a66cc819083ce6fcaf5042af6 |
completed | April 10, 2026, 3:50 p.m. |
Created at: April 8, 2026, 9:52 p.m.