Triple
T36549931
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shire Reckoning |
E901232
|
entity |
| Predicate | hasNumberOfDaysPerYear |
P64465
|
FINISHED |
| Object | 365 |
—
|
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: 365 | Statement: [Shire Reckoning, hasNumberOfDaysPerYear, 365]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfDaysPerYear Context triple: [Shire Reckoning, hasNumberOfDaysPerYear, 365]
-
A.
additionalDaysPerYear
Indicates the number of extra days added each year to a base or standard duration.
-
B.
hasNumberOfDaysIn13thMonth
Indicates the specific count of days that occur in the thirteenth month of a given calendar or time system.
-
C.
hasDayCount
chosen
Indicates that an entity is associated with a specific number of days, expressing the duration or count of days related to it.
-
D.
hasDayCountCommonYear
Indicates that something has a specified number of days as it occurs in a common (non-leap) year.
-
E.
hasNumberOfDaysIn13thMonthLeapYear
Indicates the specific count of days that occur in the thirteenth month of a leap year.
- 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_69f76e61217081908b79d610fe67b013 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69ff16775a9881909d26dbc1f0ef3e1c |
completed | May 9, 2026, 11:11 a.m. |
| PD | Predicate disambiguation | batch_69ff158e61708190a1c581d0d306cfce |
completed | May 9, 2026, 11:07 a.m. |
Created at: May 3, 2026, 4:11 p.m.