Triple
T12556350
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fernanda |
E295226
|
entity |
| Predicate | relatedName |
P3889
|
FINISHED |
| Object | Fernande |
E990807
|
NE 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: Fernande | Statement: [Fernanda, relatedName, Fernande]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fernande Context triple: [Fernanda, relatedName, Fernande]
-
A.
Fernande
chosen
Fernande is a feminine given name, primarily used in French-speaking regions, that is a variant of the name Fernanda.
-
B.
Fernande Olivier
Fernande Olivier was a French artist’s model and memoirist best known as Pablo Picasso’s early muse during his formative Paris years.
-
C.
Fernande Barrey
Fernande Barrey was a French artist’s model and painter active in early 20th-century Paris, known for her connections to the Montparnasse artistic milieu.
-
D.
Fernande Albany
Fernande Albany was a French actress of the early 20th century, known for her roles in silent films.
-
E.
Fernande de Latour
Fernande de Latour was a co-founder of California’s historic Beaulieu Vineyard, helping establish one of Napa Valley’s earliest and most influential wineries.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d6ad9cac2c81908e8a7bed82d1e21d |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d95490d2708190857f0cb9b8dd6a30 |
completed | April 10, 2026, 7:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f65eb538388190b9fb78306fbab2f3 |
completed | May 2, 2026, 8:29 p.m. |
Created at: April 8, 2026, 11:47 p.m.