Triple
T8450470
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sylvie’s Love |
E199785
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object | Sylvie |
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: Sylvie | Statement: [Sylvie’s Love, mainCharacter, Sylvie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sylvie Context triple: [Sylvie’s Love, mainCharacter, Sylvie]
-
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.
Yvaine
Yvaine is the fallen star and central heroine of Neil Gaiman’s fantasy novel (and its film adaptation) "Stardust," whose journey intertwines magic, romance, and adventure.
-
C.
Sybille
Sybille was a French frigate that took part in the early 19th-century naval engagement known as the Battle of San Domingo.
-
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.
Elysette
Elysette is the official residence of the Minister-President of Wallonia, located in Namur, Belgium.
- 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_69ca8318231881908fd1bc1c4d45d286 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe44707b88190b3d8b30c45ef4496 |
completed | March 31, 2026, 3:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce1dd14484819082f0319455011a22 |
completed | April 2, 2026, 7:42 a.m. |
Created at: March 30, 2026, 6:09 p.m.