Triple
T3590436
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | French Republican Calendar |
E76011
|
entity |
| Predicate | themeOfMonthNames |
P49572
|
FINISHED |
| Object | seasons and agricultural cycles |
—
|
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: seasons and agricultural cycles | Statement: [French Republican Calendar, themeOfMonthNames, seasons and agricultural cycles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: themeOfMonthNames Context triple: [French Republican Calendar, themeOfMonthNames, seasons and agricultural cycles]
-
A.
monthObserved
Indicates the month during which an event, observation, or measurement took place.
-
B.
moonNamingTheme
Indicates that one entity serves as the thematic basis or inspiration for how another entity’s moons are named.
-
C.
monthNumber
Indicates the numerical position of a month within a calendar year (e.g., January = 1, February = 2, etc.).
-
D.
13thMonthName
Indicates that an entity is identified as the name of a thirteenth month in a calendar system.
-
E.
hasSeasonTheme
Indicates that something is associated with or characterized by a particular seasonal theme.
- 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_69ad85d8042081908af94a04c410dec0 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc13c9514819096adf60b15016b8b |
completed | March 8, 2026, 6:34 p.m. |
| PD | Predicate disambiguation | batch_69adb839b4e08190b1c0d611cccb11ae |
completed | March 8, 2026, 5:56 p.m. |
| PDg | Predicate description generation | batch_69adb902e61c81908f10494f828e260f |
completed | March 8, 2026, 5:59 p.m. |
Created at: March 8, 2026, 3:22 p.m.