Triple
T207801
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gregorian calendar (Western churches) |
E4645
|
entity |
| Predicate | hasDayCountLeapYear |
P9862
|
FINISHED |
| Object | 366 |
—
|
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: 366 | Statement: [Gregorian calendar (Western churches), hasDayCountLeapYear, 366]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDayCountLeapYear Context triple: [Gregorian calendar (Western churches), hasDayCountLeapYear, 366]
-
A.
hasLeapYearMonthCount
Indicates the number of months in a calendar system specifically during a leap year.
-
B.
hasLeapMonth
Indicates that a given calendar year includes an extra (intercalary) month beyond the standard set of months.
-
C.
hasLeapYearFrequency
Indicates how often leap years occur within a given temporal pattern or calendar system.
-
D.
hasCommonYearMonthCount
Indicates that two entities share the same number of distinct year–month combinations associated with them.
-
E.
hasAverageMonthLength
Indicates that an entity is associated with a specified average length of a month, typically expressed in days.
- 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_69a25737567c81908f9c505300239181 |
completed | Feb. 28, 2026, 2:47 a.m. |
| NER | Named-entity recognition | batch_69a25e8b9b908190b69a3f0594b95f7e |
completed | Feb. 28, 2026, 3:18 a.m. |
| PD | Predicate disambiguation | batch_69a25b4e3c2881908d83e8218aa9f2d9 |
completed | Feb. 28, 2026, 3:04 a.m. |
| PDg | Predicate description generation | batch_69a25e8ade9481908d5570f6a255ee50 |
completed | Feb. 28, 2026, 3:18 a.m. |
Created at: Feb. 28, 2026, 2:51 a.m.