Triple
T7343080
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Silvia |
E169305
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Silvie |
E170253
|
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: Silvie | Statement: [Silvia, hasVariant, Silvie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Silvie Context triple: [Silvia, hasVariant, Silvie]
-
A.
Sylvie
chosen
Sylvie is a feminine given name, often used as a French variant of Sylvia, associated with meanings related to the forest or woods.
-
B.
Sybille
Sybille was a French frigate that took part in the early 19th-century naval engagement known as the Battle of San Domingo.
-
C.
Liliane
Liliane is a feminine given name of French origin, notably borne by French heiress and businesswoman Liliane Bettencourt.
-
D.
Marzelline
Marzelline is a character in Beethoven's opera "Fidelio," portrayed as the jailer Rocco’s daughter who becomes romantically entangled with the disguised heroine.
-
E.
Bauline
Bauline is a small coastal town in Newfoundland and Labrador, Canada, located on the Avalon Peninsula near St. John’s.
- 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_69c68a57710481909f0c1f3c6ebdb6f2 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f0db2db8819088c4bed5d65571f6 |
completed | March 27, 2026, 9:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7fa8a2a908190886e11a7d8df6c5e |
completed | March 28, 2026, 3:58 p.m. |
Created at: March 27, 2026, 3:04 p.m.