Triple
T84605
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Holy Eucharist |
E1701
|
entity |
| Predicate | frequencyVariesTo |
P85
|
FINISHED |
| Object | occasional celebration |
—
|
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: occasional celebration | Statement: [Holy Eucharist, frequencyVariesTo, occasional celebration]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: frequencyVariesTo Context triple: [Holy Eucharist, frequencyVariesTo, occasional celebration]
-
A.
frequency
chosen
Indicates how often an event, action, or relationship occurs within a given period or context.
-
B.
locationVariesWith
Indicates that the location of one entity changes in dependence on, or as a function of, changes in another entity.
-
C.
frequencyBand
Indicates the specific range of frequencies within which a signal, measurement, or phenomenon is defined or operates.
-
D.
awardedFrequency
Indicates how often an award or recognition is given within a specified time period.
-
E.
spreadingRateType
Indicates the manner or category of how quickly or in what way something spreads or propagates.
- 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_69a24c8150408190910a693eb51c1f71 |
completed | Feb. 28, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69a24f4e73c081908d2da146226ef05e |
completed | Feb. 28, 2026, 2:13 a.m. |
| PD | Predicate disambiguation | batch_69a24eb469548190b38c24e81f36c838 |
completed | Feb. 28, 2026, 2:11 a.m. |
Created at: Feb. 28, 2026, 2:06 a.m.