Triple
T3189965
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cirey, Kingdom of France |
E66796
|
entity |
| Predicate | frequentVisitors |
P1097
|
FINISHED |
| Object | Enlightenment intellectuals |
—
|
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: Enlightenment intellectuals | Statement: [Cirey, Kingdom of France, frequentVisitors, Enlightenment intellectuals]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: frequentVisitors Context triple: [Cirey, Kingdom of France, frequentVisitors, Enlightenment intellectuals]
-
A.
frequentlyVisitedBy
chosen
Indicates that an entity is regularly or often visited by another entity.
-
B.
visitorFrequency
Indicates how often a visitor comes to or interacts with a particular entity or location.
-
C.
primaryVisitors
Indicates that certain entities are the main or most important visitors associated with another entity or context.
-
D.
visitorCount
Indicates the number of visitors associated with a particular entity, context, or time period.
-
E.
isFrequently
Indicates that an action, state, or relationship occurs often or with high regularity between the related entities.
- 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_69ad8588ba18819086a10951c32ecb80 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada6e67e948190afbd9cc6a3ade415 |
completed | March 8, 2026, 4:42 p.m. |
| PD | Predicate disambiguation | batch_69ad9e04290481909092ddfbe6fdaabc |
completed | March 8, 2026, 4:04 p.m. |
Created at: March 8, 2026, 3:07 p.m.