Triple
T3052797
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | September |
E60409
|
entity |
| Predicate | hasDayCountRangeInYear |
P15776
|
FINISHED |
| Object | days 244–273 in common year |
—
|
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: days 244–273 in common year | Statement: [September, hasDayCountRangeInYear, days 244–273 in common year]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDayCountRangeInYear Context triple: [September, hasDayCountRangeInYear, days 244–273 in common year]
-
A.
hasDayNumberRange
chosen
Indicates that something is associated with a contiguous range of day numbers between a specified minimum and maximum value.
-
B.
hasDayCountCommonYear
Indicates that something has a specified number of days as it occurs in a common (non-leap) year.
-
C.
hasDayCountLeapYear
Indicates that the associated day count value applies specifically to a leap year.
-
D.
hasCommonYearMonthCount
Indicates that two entities share the same number of distinct year–month combinations associated with them.
-
E.
hasNumberOfDaysIn13thMonth
Indicates the specific count of days that occur in the thirteenth month of a given calendar or time system.
- 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_69ad8578137c81908259dcb27c7d6d7c |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ad9bf3c52c8190bbe8e5cb98c21715 |
completed | March 8, 2026, 3:55 p.m. |
| PD | Predicate disambiguation | batch_69ad962195388190856013a2519c2b0f |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 3:01 p.m.