Triple
T15454508
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ventôse |
E371733
|
entity |
| Predicate | hasDayNamingScheme |
P33973
|
FINISHED |
| Object | agricultural plants |
—
|
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: agricultural plants | Statement: [Ventôse, hasDayNamingScheme, agricultural plants]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDayNamingScheme Context triple: [Ventôse, hasDayNamingScheme, agricultural plants]
-
A.
hasDayNameSystem
chosen
Indicates that an entity employs or is associated with a particular system for naming or designating days.
-
B.
hasFirstDayNumber
Indicates that an entity is associated with a specific numerical value representing the first day in a sequence, period, or schedule.
-
C.
hasNameDayType
Indicates that an entity’s name day is classified under a specific type or category of name day.
-
D.
hasDayCount
Indicates that an entity is associated with a specific number of days, expressing the duration or count of days related to it.
-
E.
hasDayCountPattern
Indicates a relationship where something follows or is associated with a specific pattern in the number or arrangement of days.
- 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.