Lëkkaloo entite ak quiz dindi lu leer

Sooy def quiz bi, tontu yi ak leeral yi dañuy feeñ.

1. Lan mooy lëkkalekaayu entite biy lëkkale ab mbind?
   • Xëtu web bu bari
   • Taggat yaram bu bees
   • Jubbanti ortograafi
   • Duggal bu amul fenn ci base de connaissance
2. Ci wax ji 'sosiete Apple genne na telefon', lan mooy liggéeyu dindi mbir yi?
   • Xalaatal Apple mooy meññeef mi, du liggéeyukaay bi
   • Xalaatal Apple mooy liggéeyukaay xarala yi, du meññeef yi
   • Tekki Apple ci beneen làkk
   • Lim araf yi ci Apple
3. Luy njariñu etape defar kàndidaa yi?
   • Ngir bind xët wu bees
   • Ngir efaase kàddu yu jaxasoo
   • Ngir am limu entite yu mëna méngoo
   • Ngir tekki mbind mi
4. Ban cër la bi-encoder di def ci lëkkaloo entite yu bees yi?
   • Seetlu bu gaaw jaaraleko ci ay samp yu wuute ngir wax ak entite
   • Etiketu loxo bu yeex ci bepp wax
   • Defar nataali entite
   • Encrypter base de connaissance
5. Luy klaas NIL ci lëkkaloo entite?
   • Entite bi gëna siiw
   • Mention bu amul benn duggal ci xam-xam bu méngoo
   • ñaari entite
   • Jumtukaay ci tàggat yaram
6. How can document-level coherence help an entity-linking system?
   • By guaranteeing that every mention has the same entity identifier
   • By proving every document discusses only one topic
   • By removing the need to evaluate individual mention contexts
   • By considering whether candidate assignments fit the document context and one another
7. After fast candidate retrieval, what information does a cross-encoder jointly read for entity-linking reranking?
   • The mention's context and a candidate entity's description
   • Only the entity's numeric identifier with no text
   • Only the two input filenames
   • Only the number of images in the knowledge base
8. If an entity-linking pipeline never proposes the span 'Apple' for analysis, which initial stage has missed that mention?
   • The final candidate reranker only
   • The image-compression stage
   • Mention detection
   • The knowledge base's output filename formatter