Triple
T1480355
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sylvia |
E30938
|
entity |
| Predicate | hasDiminutive |
P456
|
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: [Sylvia, hasDiminutive, Sylvie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sylvie Context triple: [Sylvia, hasDiminutive, 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.
Suzanne
"Suzanne" is a renowned song by Leonard Cohen, celebrated for its poetic lyrics and haunting melody.
-
C.
Pierrette
Pierrette is a French feminine given name, traditionally considered the female form of Pierre.
-
D.
Louise
Louise is a feminine given name of French origin, traditionally associated with nobility and widely used in many European and English-speaking countries.
-
E.
Sibyl
Sibyl is a prophetic figure from ancient Greco-Roman tradition, typically depicted as a woman endowed with divine insight and the power of inspired oracles.
- 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_69a498fe55a88190ab7f9e40ace88e49 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c674cc9c819088fc9146c7a7a914 |
completed | March 1, 2026, 11:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad2940a44c8190967a62781cca0306 |
completed | March 8, 2026, 7:46 a.m. |
Created at: March 1, 2026, 8:11 p.m.