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chatbots-python's Introduction

Consulte a tabela a seguir para saber o significado de cada atributo que eximos no código.

TEXTO Texto ou palavra que está sendo processado
LEMMA Forma raiz da palavra que está sendo processada.
POS Parte de fala da palavra.
TAG Expressa a parte da fala (por exemplo, VERB) e algumas informações morfológicas (por exemplo, que o verbo está no passado).
DEP Dependência sintática (isto é, a relação entre os tokens).
SHAPE Forma da palavra (por exemplo, letras maiúsculas, pontuação, formato de dígitos).
ALPHA O token é um caractere alfabético?.
STOP A palavra é uma stopword ou faz parte de uma stop list?

Siglas

Sigla Significado
NLP Natural Language Processing
NER Named-Entity Recognition
NLU Natural Language Understanding
DOB Date of Birth
PDV Post Deployment Verification

Porque a marcação POS é necessária em chatbots?

  • Para reduzir a complexidade de criação de um texto que não possa ser ensinado ou que seja ensinado com pouca segurança.

Stemização e lematização

  • idk

Os modelo treinados com o acervo OntoNotes 5 dão suporte aos tipos de entidades a seguir

TIPO DESCRIÇÃO
PERSON People, including fictional
NORP Nationalities or religious or political groups
FACILITY Buildings, airports, highways, bridges, etc.
ORGANIZATION Companies, agencies, institutions, etc.
GPE Countries, cities, states
LOCATION Non-GPE locations, mountain ranges, bodies of water
PRODUCT Vehicles, weapons, foods, etc. (Not services)
EVENT Named hurricanes, battles, wars, sports events, etc.
WORK OF ART Titles of books, songs, etc.
LAW Named documents made into laws
LANGUAGE Any named language
DATE Absolute or relative dates or periods
PERCENT Percentage (including “%”)
MONEY Monetary values, including unit
QUANTITY Measurements, as of weight or distance
ORDINAL “first”, “second”
CARDINAL Numerals that do not fall under another type

OntoNotes Release 5.0

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