spaCy/website/docs/api/lexeme.jade

//- 💫 DOCS > API > LEXEME

include ../../_includes/_mixins

p
    |  An entry in the vocabulary. A #[code Lexeme] has no string context – it's
    |  a word type, as opposed to a word token. It therefore has no
    |  part-of-speech tag, dependency parse, or lemma (if lemmatization depends
    |  on the part-of-speech tag).

+h(2, "init") Lexeme.__init__
    +tag method

p Create a #[code Lexeme] object.

+table(["Name", "Type", "Description"])
    +row
        +cell #[code vocab]
        +cell #[code Vocab]
        +cell The parent vocabulary.

    +row
        +cell #[code orth]
        +cell int
        +cell The orth id of the lexeme.

    +footrow
        +cell returns
        +cell #[code Lexeme]
        +cell The newly constructed object.

+h(2, "set_flag") Lexeme.set_flag
    +tag method

p Change the value of a boolean flag.

+aside-code("Example").
    COOL_FLAG = nlp.vocab.add_flag(lambda text: False)
    nlp.vocab[u'spaCy'].set_flag(COOL_FLAG, True)

+table(["Name", "Type", "Description"])
    +row
        +cell #[code flag_id]
        +cell int
        +cell The attribute ID of the flag to set.

    +row
        +cell #[code value]
        +cell bool
        +cell The new value of the flag.

+h(2, "check_flag") Lexeme.check_flag
    +tag method

p Check the value of a boolean flag.

+aside-code("Example").
    is_my_library = lambda text: text in ['spaCy', 'Thinc']
    MY_LIBRARY = nlp.vocab.add_flag(is_my_library)
    assert nlp.vocab[u'spaCy'].check_flag(MY_LIBRARY) == True

+table(["Name", "Type", "Description"])
    +row
        +cell #[code flag_id]
        +cell int
        +cell The attribute ID of the flag to query.

    +footrow
        +cell returns
        +cell bool
        +cell The value of the flag.

+h(2, "similarity") Lexeme.similarity
    +tag method
    +tag-model("vectors")

p Compute a semantic similarity estimate. Defaults to cosine over vectors.

+aside-code("Example").
    apple = nlp.vocab[u'apple']
    orange = nlp.vocab[u'orange']
    apple_orange = apple.similarity(orange)
    orange_apple = orange.similarity(apple)
    assert apple_orange == orange_apple

+table(["Name", "Type", "Description"])
    +row
        +cell other
        +cell -
        +cell
            |  The object to compare with. By default, accepts #[code Doc],
            |  #[code Span], #[code Token] and #[code Lexeme] objects.

    +footrow
        +cell returns
        +cell float
        +cell A scalar similarity score. Higher is more similar.


+h(2, "has_vector") Lexeme.has_vector
    +tag property
    +tag-model("vectors")

p
    |  A boolean value indicating whether a word vector is associated with the
    |  lexeme.

+aside-code("Example").
    apple = nlp.vocab[u'apple']
    assert apple.has_vector

+table(["Name", "Type", "Description"])
    +footrow
        +cell returns
        +cell bool
        +cell Whether the lexeme has a vector data attached.

+h(2, "vector") Lexeme.vector
    +tag property
    +tag-model("vectors")

p A real-valued meaning representation.

+aside-code("Example").
    apple = nlp.vocab[u'apple']
    assert apple.vector.dtype == 'float32'
    assert apple.vector.shape == (300,)

+table(["Name", "Type", "Description"])
    +footrow
        +cell returns
        +cell #[code numpy.ndarray[ndim=1, dtype='float32']]
        +cell A 1D numpy array representing the lexeme's semantics.

+h(2, "vector_norm") Lexeme.vector_norm
    +tag property
    +tag-model("vectors")

p The L2 norm of the lexeme's vector representation.

+aside-code("Example").
    apple = nlp.vocab[u'apple']
    pasta = nlp.vocab[u'pasta']
    apple.vector_norm # 7.1346845626831055
    pasta.vector_norm # 7.759851932525635
    assert apple.vector_norm != pasta.vector_norm

+table(["Name", "Type", "Description"])
    +footrow
        +cell returns
        +cell float
        +cell The L2 norm of the vector representation.

+h(2, "attributes") Attributes

+table(["Name", "Type", "Description"])
    +row
        +cell #[code vocab]
        +cell #[code Vocab]
        +cell

    +row
        +cell #[code text]
        +cell unicode
        +cell Verbatim text content.

    +row
        +cell #[code lex_id]
        +cell int
        +cell ID of the lexeme's lexical type.

    +row
        +cell #[code lower]
        +cell int
        +cell Lower-case form of the word.

    +row
        +cell #[code lower_]
        +cell unicode
        +cell Lower-case form of the word.

    +row
        +cell #[code shape]
        +cell int
        +cell Transform of the word's string, to show orthographic features.

    +row
        +cell #[code shape_]
        +cell unicode
        +cell Transform of the word's string, to show orthographic features.

    +row
        +cell #[code prefix]
        +cell int
        +cell Length-N substring from the start of the word. Defaults to #[code N=1].

    +row
        +cell #[code prefix_]
        +cell unicode
        +cell Length-N substring from the start of the word. Defaults to #[code N=1].

    +row
        +cell #[code suffix]
        +cell int
        +cell Length-N substring from the end of the word. Defaults to #[code N=3].

    +row
        +cell #[code suffix_]
        +cell unicode
        +cell Length-N substring from the start of the word. Defaults to #[code N=3].

    +row
        +cell #[code is_alpha]
        +cell bool
        +cell Equivalent to #[code word.orth_.isalpha()].

    +row
        +cell #[code is_ascii]
        +cell bool
        +cell Equivalent to #[code [any(ord(c) >= 128 for c in word.orth_)]].

    +row
        +cell #[code is_digit]
        +cell bool
        +cell Equivalent to #[code word.orth_.isdigit()].

    +row
        +cell #[code is_lower]
        +cell bool
        +cell Equivalent to #[code word.orth_.islower()].

    +row
        +cell #[code is_title]
        +cell bool
        +cell Equivalent to #[code word.orth_.istitle()].

    +row
        +cell #[code is_punct]
        +cell bool
        +cell Equivalent to #[code word.orth_.ispunct()].

    +row
        +cell #[code is_space]
        +cell bool
        +cell Equivalent to #[code word.orth_.isspace()].

    +row
        +cell #[code like_url]
        +cell bool
        +cell Does the word resemble a URL?

    +row
        +cell #[code like_num]
        +cell bool
        +cell Does the word represent a number? e.g. “10.9”, “10”, “ten”, etc.

    +row
        +cell #[code like_email]
        +cell bool
        +cell Does the word resemble an email address?

    +row
        +cell #[code is_oov]
        +cell bool
        +cell Is the word out-of-vocabulary?

    +row
        +cell #[code is_stop]
        +cell bool
        +cell Is the word part of a "stop list"?

    +row
        +cell #[code lang]
        +cell int
        +cell Language of the parent vocabulary.
    +row
        +cell #[code lang_]
        +cell unicode
        +cell Language of the parent vocabulary.

    +row
        +cell #[code prob]
        +cell float
        +cell Smoothed log probability estimate of lexeme's type.

    +row
        +cell #[code sentiment]
        +cell float
        +cell A scalar value indicating the positivity or negativity of the lexeme.