Triple
T3590437
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | French Republican Calendar |
E76011
|
entity |
| Predicate | themeOfDayNames |
P33973
|
FINISHED |
| Object | plants, animals, tools, and minerals |
—
|
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: plants, animals, tools, and minerals | Statement: [French Republican Calendar, themeOfDayNames, plants, animals, tools, and minerals]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: themeOfDayNames Context triple: [French Republican Calendar, themeOfDayNames, plants, animals, tools, and minerals]
-
A.
dayName
Indicates the specific name of the day of the week associated with a given date or time.
-
B.
namesDay
Indicates that one entity is the name assigned to a particular day (such as a weekday or holiday) associated with another entity.
-
C.
weekdayEtymologyOf
Indicates that one concept is the etymological source or origin of the name of a particular weekday.
-
D.
hasDayNameSystem
chosen
Indicates that an entity employs or is associated with a particular system for naming or designating days.
-
E.
secondDayName
Indicates that one entity is the name or label assigned to the second day in a sequence of days associated with another entity.
- 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_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. |
Created at: March 8, 2026, 3:22 p.m.