Triple
T2883035
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Magha Puja |
E59439
|
entity |
| Predicate | commonPractice |
P12146
|
FINISHED |
| Object | offering food to monks |
—
|
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: offering food to monks | Statement: [Magha Puja, commonPractice, offering food to monks]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: commonPractice Context triple: [Magha Puja, commonPractice, offering food to monks]
-
A.
typicalPractice
chosen
Indicates that an action, behavior, or method is commonly or customarily done in a given context or by a given group.
-
B.
commonIn
Indicates that something frequently occurs, appears, or is found within a specified context, group, or environment.
-
C.
modernPractice
Indicates that an entity engages in or reflects a contemporary, up-to-date way of doing something, following current methods, standards, or trends.
-
D.
commonCut
Indicates that two or more entities share at least one identical segment or portion that has been cut or divided in the same way.
-
E.
moreCommonIn
Indicates that something occurs with greater frequency or prevalence in one group, context, or location than in another.
- 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_69ab4ac739188190a112f42a5a69c951 |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abe02c238881908f7a349563c388bf |
completed | March 7, 2026, 8:22 a.m. |
| PD | Predicate disambiguation | batch_69abdd15cbf08190bf7fea5ea516848a |
completed | March 7, 2026, 8:08 a.m. |
Created at: March 6, 2026, 10:03 p.m.