Span
A slice from a Doc object.
Span.__init__ method
Create a Span object from the slice doc[start : end].
| Name | Description |
|---|---|
doc | The parent document. Doc |
start | The index of the first token of the span. int |
end | The index of the first token after the span. int |
label | A label to attach to the span, e.g. for named entities. Union[str, int] |
vector | A meaning representation of the span. numpy.ndarray[ndim=1, dtype=float32] |
vector_norm | The L2 norm of the document’s vector representation. float |
kb_id | A knowledge base ID to attach to the span, e.g. for named entities. Union[str, int] |
span_id | An ID to associate with the span. Union[str, int] |
Span.__getitem__ method
Get a Token object.
| Name | Description |
|---|---|
i | The index of the token within the span. int |
| RETURNS | The token at span[i]. Token |
Get a Span object.
| Name | Description |
|---|---|
start_end | The slice of the span to get. Tuple[int, int] |
| RETURNS | The span at span[start : end]. Span |
Span.__iter__ method
Iterate over Token objects.
| Name | Description |
|---|---|
| YIELDS | A Token object. Token |
Span.__len__ method
Get the number of tokens in the span.
| Name | Description |
|---|---|
| RETURNS | The number of tokens in the span. int |
Span.set_extension classmethod
Define a custom attribute on the Span which becomes available via Span._.
For details, see the documentation on
custom attributes.
| Name | Description |
|---|---|
name | Name of the attribute to set by the extension. For example, "my_attr" will be available as span._.my_attr. str |
default | Optional default value of the attribute if no getter or method is defined. Optional[Any] |
method | Set a custom method on the object, for example span._.compare(other_span). Optional[Callable[[Span, …], Any]] |
getter | Getter function that takes the object and returns an attribute value. Is called when the user accesses the ._ attribute. Optional[Callable[[Span], Any]] |
setter | Setter function that takes the Span and a value, and modifies the object. Is called when the user writes to the Span._ attribute. Optional[Callable[[Span, Any], None]] |
force | Force overwriting existing attribute. bool |
Span.get_extension classmethod
Look up a previously registered extension by name. Returns a 4-tuple
(default, method, getter, setter) if the extension is registered. Raises a
KeyError otherwise.
| Name | Description |
|---|---|
name | Name of the extension. str |
| RETURNS | A (default, method, getter, setter) tuple of the extension. Tuple[Optional[Any], Optional[Callable], Optional[Callable], Optional[Callable]] |
Span.has_extension classmethod
Check whether an extension has been registered on the Span class.
| Name | Description |
|---|---|
name | Name of the extension to check. str |
| RETURNS | Whether the extension has been registered. bool |
Span.remove_extension classmethod
Remove a previously registered extension.
| Name | Description |
|---|---|
name | Name of the extension. str |
| RETURNS | A (default, method, getter, setter) tuple of the removed extension. Tuple[Optional[Any], Optional[Callable], Optional[Callable], Optional[Callable]] |
Span.char_span method
Create a Span object from the slice span.text[start:end]. Returns None if
the character indices don’t map to a valid span.
| Name | Description |
|---|---|
start | The index of the first character of the span. int |
end | The index of the last character after the span. int |
label | A label to attach to the span, e.g. for named entities. Union[int, str] |
kb_id | An ID from a knowledge base to capture the meaning of a named entity. Union[int, str] |
vector | A meaning representation of the span. numpy.ndarray[ndim=1, dtype=float32] |
id | Unused. Union[int, str] |
alignment_mode v3.5.1 | How character indices snap to token boundaries. Options: "strict" (no snapping), "contract" (span of all tokens completely within the character span), "expand" (span of all tokens at least partially covered by the character span). Defaults to "strict". str |
span_id v3.5.1 | An identifier to associate with the span. Union[int, str] |
| RETURNS | The newly constructed object or None. Optional[Span] |
Span.similarity methodNeeds model
Make a semantic similarity estimate. The default estimate is cosine similarity using an average of word vectors.
| Name | Description |
|---|---|
other | The object to compare with. By default, accepts Doc, Span, Token and Lexeme objects. Union[Doc,Span,Token,Lexeme] |
| RETURNS | A scalar similarity score. Higher is more similar. float |
Span.get_lca_matrix method
Calculates the lowest common ancestor matrix for a given Span. Returns LCA
matrix containing the integer index of the ancestor, or -1 if no common
ancestor is found, e.g. if span excludes a necessary ancestor.
| Name | Description |
|---|---|
| RETURNS | The lowest common ancestor matrix of the Span. numpy.ndarray[ndim=2, dtype=int32] |
Span.to_array method
Given a list of M attribute IDs, export the tokens to a numpy ndarray of
shape (N, M), where N is the length of the document. The values will be
32-bit integers.
| Name | Description |
|---|---|
attr_ids | A list of attributes (int IDs or string names) or a single attribute (int ID or string name). Union[int, str, List[Union[int, str]]] |
| RETURNS | The exported attributes as a numpy array. Union[numpy.ndarray[ndim=2, dtype=uint64],numpy.ndarray[ndim=1, dtype=uint64]] |
Span.ents propertyNeeds model
The named entities that fall completely within the span. Returns a tuple of
Span objects.
| Name | Description |
|---|---|
| RETURNS | Entities in the span, one Span per entity. Tuple[Span, …] |
Span.noun_chunks propertyNeeds model
Iterate over the base noun phrases in the span. Yields base noun-phrase Span
objects, if the document has been syntactically parsed. A base noun phrase, or
“NP chunk”, is a noun phrase that does not permit other NPs to be nested within
it – so no NP-level coordination, no prepositional phrases, and no relative
clauses.
If the noun_chunk syntax iterator
has not been implemented for the given language, a NotImplementedError is
raised.
| Name | Description |
|---|---|
| YIELDS | Noun chunks in the span. Span |
Span.as_doc method
Create a new Doc object corresponding to the Span, with a copy of the data.
When calling this on many spans from the same doc, passing in a precomputed
array representation of the doc using the array_head and array args can save
time.
| Name | Description |
|---|---|
copy_user_data | Whether or not to copy the original doc’s user data. bool |
array_head | Precomputed array attributes (headers) of the original doc, as generated by Doc._get_array_attrs(). Tuple |
array | Precomputed array version of the original doc as generated by Doc.to_array. numpy.ndarray |
| RETURNS | A Doc object of the Span’s content. Doc |
Span.root propertyNeeds model
The token with the shortest path to the root of the sentence (or the root itself). If multiple tokens are equally high in the tree, the first token is taken.
| Name | Description |
|---|---|
| RETURNS | The root token. Token |
Span.conjuncts propertyNeeds model
A tuple of tokens coordinated to span.root.
| Name | Description |
|---|---|
| RETURNS | The coordinated tokens. Tuple[Token, …] |
Span.lefts propertyNeeds model
Tokens that are to the left of the span, whose heads are within the span.
| Name | Description |
|---|---|
| YIELDS | A left-child of a token of the span. Token |
Span.rights propertyNeeds model
Tokens that are to the right of the span, whose heads are within the span.
| Name | Description |
|---|---|
| YIELDS | A right-child of a token of the span. Token |
Span.n_lefts propertyNeeds model
The number of tokens that are to the left of the span, whose heads are within the span.
| Name | Description |
|---|---|
| RETURNS | The number of left-child tokens. int |
Span.n_rights propertyNeeds model
The number of tokens that are to the right of the span, whose heads are within the span.
| Name | Description |
|---|---|
| RETURNS | The number of right-child tokens. int |
Span.subtree propertyNeeds model
Tokens within the span and tokens which descend from them.
| Name | Description |
|---|---|
| YIELDS | A token within the span, or a descendant from it. Token |
Span.has_vector propertyNeeds model
A boolean value indicating whether a word vector is associated with the object.
| Name | Description |
|---|---|
| RETURNS | Whether the span has a vector data attached. bool |
Span.vector propertyNeeds model
A real-valued meaning representation. Defaults to an average of the token vectors.
| Name | Description |
|---|---|
| RETURNS | A 1-dimensional array representing the span’s vector. `numpy.ndarray[ndim=1, dtype=float32] |
Span.vector_norm propertyNeeds model
The L2 norm of the span’s vector representation.
| Name | Description |
|---|---|
| RETURNS | The L2 norm of the vector representation. float |
Span.sent propertyNeeds model
The sentence span that this span is a part of. This property is only available
when sentence boundaries have been set on the
document by the parser, senter, sentencizer or some custom function. It
will raise an error otherwise.
If the span happens to cross sentence boundaries, only the first sentence will be returned. If it is required that the sentence always includes the full span, the result can be adjusted as such:
| Name | Description |
|---|---|
| RETURNS | The sentence span that this span is a part of. Span |
Span.sents propertyv3.2.1Needs model
Returns a generator over the sentences the span belongs to. This property is
only available when sentence boundaries have
been set on the document by the parser, senter, sentencizer or some custom
function. It will raise an error otherwise.
If the span happens to cross sentence boundaries, all sentences the span overlaps with will be returned.
| Name | Description |
|---|---|
| RETURNS | A generator yielding sentences this Span is a part of Iterable[Span] |
Attributes
| Name | Description |
|---|---|
doc | The parent document. Doc |
tensor | The span’s slice of the parent Doc’s tensor. numpy.ndarray |
start | The token offset for the start of the span. int |
end | The token offset for the end of the span. int |
start_char | The character offset for the start of the span. int |
end_char | The character offset for the end of the span. int |
text | A string representation of the span text. str |
text_with_ws | The text content of the span with a trailing whitespace character if the last token has one. str |
orth | ID of the verbatim text content. int |
orth_ | Verbatim text content (identical to Span.text). Exists mostly for consistency with the other attributes. str |
label | The hash value of the span’s label. int |
label_ | The span’s label. str |
lemma_ | The span’s lemma. Equivalent to "".join(token.text_with_ws for token in span). str |
kb_id | The hash value of the knowledge base ID referred to by the span. int |
kb_id_ | The knowledge base ID referred to by the span. str |
ent_id | The hash value of the named entity the root token is an instance of. int |
ent_id_ | The string ID of the named entity the root token is an instance of. str |
id | The hash value of the span’s ID. int |
id_ | The span’s ID. str |
sentiment | A scalar value indicating the positivity or negativity of the span. float |
_ | User space for adding custom attribute extensions. Underscore |