Triple
T5558351
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Teves |
E145703
|
entity |
| Predicate | occursInGregorianMonths |
P16936
|
FINISHED |
| Object | December |
—
|
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: December | Statement: [Teves, occursInGregorianMonths, December]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: occursInGregorianMonths Context triple: [Teves, occursInGregorianMonths, December]
-
A.
occursAfterLeapMonthInLeapYears
Indicates that the referenced event or time period takes place after the leap month specifically in years that are designated as leap years.
-
B.
correspondsRoughlyToGregorianMonths
chosen
Indicates that one or more time periods or units align approximately, but not exactly, with specific months in the Gregorian calendar.
-
C.
hasNumberOfDaysIn13thMonth
Indicates the specific count of days that occur in the thirteenth month of a given calendar or time system.
-
D.
hasLeapMonth
Indicates that a given calendar year includes an extra (intercalary) month beyond the standard set of months.
-
E.
hasCommonYearMonthCount
Indicates that two entities share the same number of distinct year–month combinations associated with them.
- 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_69c008fcaf788190bafa02a1917ee73b |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c0201529a88190bf0135e032b048ea |
completed | March 22, 2026, 5 p.m. |
| PD | Predicate disambiguation | batch_69c01b10bbf8819098655839c03b7832 |
completed | March 22, 2026, 4:38 p.m. |
Created at: March 22, 2026, 3:36 p.m.