Triple
T20467065
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sophie Vavasseur |
E502078
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Sophie |
—
|
NE NERFINISHED |
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: Sophie | Statement: [Sophie Vavasseur, givenName, Sophie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sophie Context triple: [Sophie Vavasseur, givenName, Sophie]
-
A.
Sophie
chosen
Sophie is a feminine given name of Greek origin, commonly used in many countries and meaning "wisdom."
-
B.
Sophie
Sophie is a character in Kazuo Ishiguro’s surreal novel "The Unconsoled," involved in the emotionally fraught relationships surrounding the pianist protagonist, Ryder.
-
C.
Sophie
Sophie is an experimental pop producer and musician known for her innovative, hyper-stylized electronic sound and influential work in the PC Music scene.
-
D.
Sophy
Sophy is a central character in William Styron’s memoir-novel "Darkness Visible," which explores his struggle with clinical depression.
-
E.
Sophia
"Sophia" is a lesser-known literary work by British novelist Anthony Hope, best known for his adventure classic "The Prisoner of Zenda."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4ae5f1081908768b0c9a3a0bf38 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6995d9d1c81909ee223a35a0850ba |
completed | April 20, 2026, 9:23 p.m. |
Created at: April 16, 2026, 11:33 a.m.