Triple
T14242375
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anne-Catherine de Ligniville |
E353041
|
entity |
| Predicate | typeOfSalon |
P113366
|
FINISHED |
| Object | literary salon |
—
|
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: literary salon | Statement: [Anne-Catherine de Ligniville, typeOfSalon, literary salon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfSalon Context triple: [Anne-Catherine de Ligniville, typeOfSalon, literary salon]
-
A.
aimOfSalon
Indicates that a particular goal, purpose, or objective is the intended focus or mission of a salon.
-
B.
maintainedSalonIn
Indicates that an entity operated or hosted a salon (a regular social or intellectual gathering) in a particular location.
-
C.
cosmeticCategory
Indicates that one entity is classified as belonging to a particular cosmetic or beauty product category defined by the other entity.
-
D.
hasGrooming
Indicates that one entity performs grooming behavior on, or receives grooming from, another entity.
-
E.
serviceOf
Indicates that one entity performs, provides, or fulfills a function or duty on behalf of another entity.
- 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_69d8278adc7c8190a9218d69bce3c4e6 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de6244ad188190b9d9db7914240410 |
completed | April 14, 2026, 3:50 p.m. |
| PD | Predicate disambiguation | batch_69de05bf069c8190b69f00f00f5eb126 |
completed | April 14, 2026, 9:15 a.m. |
| PDg | Predicate description generation | batch_69de239bd0f48190ada38c0261e0ef3c |
completed | April 14, 2026, 11:23 a.m. |
Created at: April 10, 2026, 1:08 a.m.