Triple
T15454656
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sansculottides |
E371737
|
entity |
| Predicate | totalDaysInYearWithSansculottides |
P49552
|
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: [Sansculottides, totalDaysInYearWithSansculottides, 365]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: totalDaysInYearWithSansculottides Context triple: [Sansculottides, totalDaysInYearWithSansculottides, 365]
-
A.
yearInFrenchRepublicanCalendar
Indicates the specific year of an event or entity as expressed in the French Republican calendar system.
-
B.
additionalDaysPerYear
chosen
Indicates the number of extra days added each year to a base or standard duration.
-
C.
specialDaysCount
Indicates the number of special or designated days associated with an entity or time period.
-
D.
dateInFrenchRepublicanCalendar
Indicates that a given date is expressed according to the French Republican (Revolutionary) calendar system rather than another calendar.
-
E.
hasDayCountCommonYear
Indicates that something has a specified number of days as it occurs in a common (non-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_69d85cc8bd308190886949510b42e764 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03f131b1481909ff099c3b844ee07 |
completed | April 16, 2026, 1:44 a.m. |
| PD | Predicate disambiguation | batch_69ded28276f481908c2038bb301e57cf |
completed | April 14, 2026, 11:49 p.m. |
Created at: April 10, 2026, 3:31 a.m.