Awoye-ọrọ Tokenization adanwo

Awọn idahun ati awọn alaye han bi o ṣe n mu ibeere naa.

1. Awọn aropin fokabulari wo ni o ṣeduro aṣoju awọn fọọmu ọrọ toje nipasẹ awọn ege atunlo kekere?
   • Every smaller piece necessarily has one unique dictionary meaning
   • A finite word-only vocabulary cannot allocate an entry to every possible word form
   • A subword model requires no numerical input representation
   • Whole-word vocabularies cannot contain any common word
2. Eyi ti subword tokenizer wo ni atilẹba BERT lilo?
   • A word-only alphabetical index
   • A mandatory one-byte-per-word lookup
   • WordPiece
   • An image-pixel segmentation network
3. Iru ìpele wo ni o ṣe samisi awọn ege itesiwaju ti inu ni apejọ WordPiece ti a tẹjade BERT?
   • ##
   • A required trailing full stop
   • A leading plus sign on every whole word
   • Capitalization of every suffix
4. Ohun-ini mimu-imudaniloju SentencePiece wo ni o ṣe atilẹyin ọrọ laisi awọn aala ọrọ alafo funfun?
   • It requires every word to have spaces on both sides
   • It translates every sentence into English before segmentation
   • It deletes all non-Latin characters before training
   • It can train from raw sentences without language-specific word pre-tokenization
5. Kini ajeku ọrọ-ọrọ kọọkan ni ipari ṣe maapu si ṣaaju ki o to de awoṣe naa?
   • Awọ kan
   • Nẹtiwọọki nkankikan lọtọ
   • ID odidi kan
   • Agekuru ohun
6. If related word forms share an available vocabulary piece, what can that sharing support?
   • A guarantee that every token is a correct linguistic morpheme
   • Reuse of the representation associated with that piece
   • Deletion of every differing suffix from the original input
   • A requirement that all related words receive the same complete ID sequence
7. How does Unigram vocabulary training differ from BPE's bottom-up pair merging?
   • It requires a human dictionary definition for every piece
   • It only merges the most frequent pair until the corpus is one token
   • It permanently removes all character-level coverage regardless of configuration
   • It starts with candidate pieces and prunes them according to an objective
8. Why should SentencePiece not be treated as another name for the Unigram algorithm?
   • It is a library that supports both Unigram and BPE models
   • It is the name of BERT's ## continuation marker
   • It is a universal ID-to-word table shared by every model
   • It only implements whole-word splitting on English spaces