spaCy/spacy/tokens/span.pyx

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# cython: profile=False
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cimport numpy as np
import copy
import warnings
import numpy
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from thinc.api import get_array_module
from ..attrs cimport *
from ..attrs cimport ORTH, attr_id_t
from ..lexeme cimport Lexeme
from ..structs cimport TokenC
from ..symbols cimport dep
from ..typedefs cimport attr_t, hash_t
from .doc cimport _get_lca_matrix, get_token_attr
from .token cimport Token
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from ..errors import Errors, Warnings
from ..util import normalize_slice
from .underscore import Underscore, get_ext_args
cdef class Span:
"""A slice from a Doc object.
DOCS: https://spacy.io/api/span
"""
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@classmethod
def set_extension(cls, name, **kwargs):
"""Define a custom attribute which becomes available as `Span._`.
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name (str): Name of the attribute to set.
default: Optional default value of the attribute.
getter (callable): Optional getter function.
setter (callable): Optional setter function.
method (callable): Optional method for method extension.
force (bool): Force overwriting existing attribute.
DOCS: https://spacy.io/api/span#set_extension
USAGE: https://spacy.io/usage/processing-pipelines#custom-components-attributes
"""
if cls.has_extension(name) and not kwargs.get("force", False):
raise ValueError(Errors.E090.format(name=name, obj="Span"))
Underscore.span_extensions[name] = get_ext_args(**kwargs)
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@classmethod
def get_extension(cls, name):
"""Look up a previously registered extension by name.
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name (str): Name of the extension.
RETURNS (tuple): A `(default, method, getter, setter)` tuple.
DOCS: https://spacy.io/api/span#get_extension
"""
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return Underscore.span_extensions.get(name)
@classmethod
def has_extension(cls, name):
"""Check whether an extension has been registered.
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name (str): Name of the extension.
RETURNS (bool): Whether the extension has been registered.
DOCS: https://spacy.io/api/span#has_extension
"""
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return name in Underscore.span_extensions
@classmethod
def remove_extension(cls, name):
"""Remove a previously registered extension.
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name (str): Name of the extension.
RETURNS (tuple): A `(default, method, getter, setter)` tuple of the
removed extension.
DOCS: https://spacy.io/api/span#remove_extension
"""
if not cls.has_extension(name):
raise ValueError(Errors.E046.format(name=name))
return Underscore.span_extensions.pop(name)
def __cinit__(self, Doc doc, int start, int end, label=0, vector=None,
Add SpanRuler component (#9880) * Add SpanRuler component Add a `SpanRuler` component similar to `EntityRuler` that saves a list of matched spans to `Doc.spans[spans_key]`. The matches from the token and phrase matchers are deduplicated and sorted before assignment but are not otherwise filtered. * Update spacy/pipeline/span_ruler.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Fix cast * Add self.key property * Use number of patterns as length * Remove patterns kwarg from init * Update spacy/tests/pipeline/test_span_ruler.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Add options for spans filter and setting to ents * Add `spans_filter` option as a registered function' * Make `spans_key` optional and if `None`, set to `doc.ents` instead of `doc.spans[spans_key]`. * Update and generalize tests * Add test for setting doc.ents, fix key property type * Fix typing * Allow independent doc.spans and doc.ents * If `spans_key` is set, set `doc.spans` with `spans_filter`. * If `annotate_ents` is set, set `doc.ents` with `ents_fitler`. * Use `util.filter_spans` by default as `ents_filter`. * Use a custom warning if the filter does not work for `doc.ents`. * Enable use of SpanC.id in Span * Support id in SpanRuler as Span.id * Update types * `id` can only be provided as string (already by `PatternType` definition) * Update all uses of Span.id/ent_id in Doc * Rename Span id kwarg to span_id * Update types and docs * Add ents filter to mimic EntityRuler overwrite_ents * Refactor `ents_filter` to take `entities, spans` args for more filtering options * Give registered filters more descriptive names * Allow registered `filter_spans` filter (`spacy.first_longest_spans_filter.v1`) to take any number of `Iterable[Span]` objects as args so it can be used for spans filter or ents filter * Implement future entity ruler as span ruler Implement a compatible `entity_ruler` as `future_entity_ruler` using `SpanRuler` as the underlying component: * Add `sort_key` and `sort_reverse` to allow the sorting behavior to be customized. (Necessary for the same sorting/filtering as in `EntityRuler`.) * Implement `overwrite_overlapping_ents_filter` and `preserve_existing_ents_filter` to support `EntityRuler.overwrite_ents` settings. * Add `remove_by_id` to support `EntityRuler.remove` functionality. * Refactor `entity_ruler` tests to parametrize all tests to test both `entity_ruler` and `future_entity_ruler` * Implement `SpanRuler.token_patterns` and `SpanRuler.phrase_patterns` properties. Additional changes: * Move all config settings to top-level attributes to avoid duplicating settings in the config vs. `span_ruler/cfg`. (Also avoids a lot of casting.) * Format * Fix filter make method name * Refactor to use same error for removing by label or ID * Also provide existing spans to spans filter * Support ids property * Remove token_patterns and phrase_patterns * Update docstrings * Add span ruler docs * Fix types * Apply suggestions from code review Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Move sorting into filters * Check for all tokens in seen tokens in entity ruler filters * Remove registered sort key * Set Token.ent_id in a backwards-compatible way in Doc.set_ents * Remove sort options from API docs * Update docstrings * Rename entity ruler filters * Fix and parameterize scoring * Add id to Span API docs * Fix typo in API docs * Include explicit labeled=True for scorer Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
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vector_norm=None, kb_id=0, span_id=0):
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"""Create a `Span` object from the slice `doc[start : end]`.
doc (Doc): The parent document.
start (int): The index of the first token of the span.
end (int): The index of the first token after the span.
Add SpanRuler component (#9880) * Add SpanRuler component Add a `SpanRuler` component similar to `EntityRuler` that saves a list of matched spans to `Doc.spans[spans_key]`. The matches from the token and phrase matchers are deduplicated and sorted before assignment but are not otherwise filtered. * Update spacy/pipeline/span_ruler.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Fix cast * Add self.key property * Use number of patterns as length * Remove patterns kwarg from init * Update spacy/tests/pipeline/test_span_ruler.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Add options for spans filter and setting to ents * Add `spans_filter` option as a registered function' * Make `spans_key` optional and if `None`, set to `doc.ents` instead of `doc.spans[spans_key]`. * Update and generalize tests * Add test for setting doc.ents, fix key property type * Fix typing * Allow independent doc.spans and doc.ents * If `spans_key` is set, set `doc.spans` with `spans_filter`. * If `annotate_ents` is set, set `doc.ents` with `ents_fitler`. * Use `util.filter_spans` by default as `ents_filter`. * Use a custom warning if the filter does not work for `doc.ents`. * Enable use of SpanC.id in Span * Support id in SpanRuler as Span.id * Update types * `id` can only be provided as string (already by `PatternType` definition) * Update all uses of Span.id/ent_id in Doc * Rename Span id kwarg to span_id * Update types and docs * Add ents filter to mimic EntityRuler overwrite_ents * Refactor `ents_filter` to take `entities, spans` args for more filtering options * Give registered filters more descriptive names * Allow registered `filter_spans` filter (`spacy.first_longest_spans_filter.v1`) to take any number of `Iterable[Span]` objects as args so it can be used for spans filter or ents filter * Implement future entity ruler as span ruler Implement a compatible `entity_ruler` as `future_entity_ruler` using `SpanRuler` as the underlying component: * Add `sort_key` and `sort_reverse` to allow the sorting behavior to be customized. (Necessary for the same sorting/filtering as in `EntityRuler`.) * Implement `overwrite_overlapping_ents_filter` and `preserve_existing_ents_filter` to support `EntityRuler.overwrite_ents` settings. * Add `remove_by_id` to support `EntityRuler.remove` functionality. * Refactor `entity_ruler` tests to parametrize all tests to test both `entity_ruler` and `future_entity_ruler` * Implement `SpanRuler.token_patterns` and `SpanRuler.phrase_patterns` properties. Additional changes: * Move all config settings to top-level attributes to avoid duplicating settings in the config vs. `span_ruler/cfg`. (Also avoids a lot of casting.) * Format * Fix filter make method name * Refactor to use same error for removing by label or ID * Also provide existing spans to spans filter * Support ids property * Remove token_patterns and phrase_patterns * Update docstrings * Add span ruler docs * Fix types * Apply suggestions from code review Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Move sorting into filters * Check for all tokens in seen tokens in entity ruler filters * Remove registered sort key * Set Token.ent_id in a backwards-compatible way in Doc.set_ents * Remove sort options from API docs * Update docstrings * Rename entity ruler filters * Fix and parameterize scoring * Add id to Span API docs * Fix typo in API docs * Include explicit labeled=True for scorer Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
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label (Union[int, str]): A label to attach to the Span, e.g. for named
entities.
vector (ndarray[ndim=1, dtype='float32']): A meaning representation
of the span.
vector_norm (float): The L2 norm of the span's vector representation.
Add SpanRuler component (#9880) * Add SpanRuler component Add a `SpanRuler` component similar to `EntityRuler` that saves a list of matched spans to `Doc.spans[spans_key]`. The matches from the token and phrase matchers are deduplicated and sorted before assignment but are not otherwise filtered. * Update spacy/pipeline/span_ruler.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Fix cast * Add self.key property * Use number of patterns as length * Remove patterns kwarg from init * Update spacy/tests/pipeline/test_span_ruler.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Add options for spans filter and setting to ents * Add `spans_filter` option as a registered function' * Make `spans_key` optional and if `None`, set to `doc.ents` instead of `doc.spans[spans_key]`. * Update and generalize tests * Add test for setting doc.ents, fix key property type * Fix typing * Allow independent doc.spans and doc.ents * If `spans_key` is set, set `doc.spans` with `spans_filter`. * If `annotate_ents` is set, set `doc.ents` with `ents_fitler`. * Use `util.filter_spans` by default as `ents_filter`. * Use a custom warning if the filter does not work for `doc.ents`. * Enable use of SpanC.id in Span * Support id in SpanRuler as Span.id * Update types * `id` can only be provided as string (already by `PatternType` definition) * Update all uses of Span.id/ent_id in Doc * Rename Span id kwarg to span_id * Update types and docs * Add ents filter to mimic EntityRuler overwrite_ents * Refactor `ents_filter` to take `entities, spans` args for more filtering options * Give registered filters more descriptive names * Allow registered `filter_spans` filter (`spacy.first_longest_spans_filter.v1`) to take any number of `Iterable[Span]` objects as args so it can be used for spans filter or ents filter * Implement future entity ruler as span ruler Implement a compatible `entity_ruler` as `future_entity_ruler` using `SpanRuler` as the underlying component: * Add `sort_key` and `sort_reverse` to allow the sorting behavior to be customized. (Necessary for the same sorting/filtering as in `EntityRuler`.) * Implement `overwrite_overlapping_ents_filter` and `preserve_existing_ents_filter` to support `EntityRuler.overwrite_ents` settings. * Add `remove_by_id` to support `EntityRuler.remove` functionality. * Refactor `entity_ruler` tests to parametrize all tests to test both `entity_ruler` and `future_entity_ruler` * Implement `SpanRuler.token_patterns` and `SpanRuler.phrase_patterns` properties. Additional changes: * Move all config settings to top-level attributes to avoid duplicating settings in the config vs. `span_ruler/cfg`. (Also avoids a lot of casting.) * Format * Fix filter make method name * Refactor to use same error for removing by label or ID * Also provide existing spans to spans filter * Support ids property * Remove token_patterns and phrase_patterns * Update docstrings * Add span ruler docs * Fix types * Apply suggestions from code review Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Move sorting into filters * Check for all tokens in seen tokens in entity ruler filters * Remove registered sort key * Set Token.ent_id in a backwards-compatible way in Doc.set_ents * Remove sort options from API docs * Update docstrings * Rename entity ruler filters * Fix and parameterize scoring * Add id to Span API docs * Fix typo in API docs * Include explicit labeled=True for scorer Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
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kb_id (Union[int, str]): An identifier from a Knowledge Base to capture
the meaning of a named entity.
span_id (Union[int, str]): An identifier to associate with the span.
DOCS: https://spacy.io/api/span#init
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"""
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if not (0 <= start <= end <= len(doc)):
raise IndexError(Errors.E035.format(start=start, end=end, length=len(doc)))
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self.doc = doc
if isinstance(label, str):
label = doc.vocab.strings.add(label)
if isinstance(kb_id, str):
kb_id = doc.vocab.strings.add(kb_id)
Add SpanRuler component (#9880) * Add SpanRuler component Add a `SpanRuler` component similar to `EntityRuler` that saves a list of matched spans to `Doc.spans[spans_key]`. The matches from the token and phrase matchers are deduplicated and sorted before assignment but are not otherwise filtered. * Update spacy/pipeline/span_ruler.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Fix cast * Add self.key property * Use number of patterns as length * Remove patterns kwarg from init * Update spacy/tests/pipeline/test_span_ruler.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Add options for spans filter and setting to ents * Add `spans_filter` option as a registered function' * Make `spans_key` optional and if `None`, set to `doc.ents` instead of `doc.spans[spans_key]`. * Update and generalize tests * Add test for setting doc.ents, fix key property type * Fix typing * Allow independent doc.spans and doc.ents * If `spans_key` is set, set `doc.spans` with `spans_filter`. * If `annotate_ents` is set, set `doc.ents` with `ents_fitler`. * Use `util.filter_spans` by default as `ents_filter`. * Use a custom warning if the filter does not work for `doc.ents`. * Enable use of SpanC.id in Span * Support id in SpanRuler as Span.id * Update types * `id` can only be provided as string (already by `PatternType` definition) * Update all uses of Span.id/ent_id in Doc * Rename Span id kwarg to span_id * Update types and docs * Add ents filter to mimic EntityRuler overwrite_ents * Refactor `ents_filter` to take `entities, spans` args for more filtering options * Give registered filters more descriptive names * Allow registered `filter_spans` filter (`spacy.first_longest_spans_filter.v1`) to take any number of `Iterable[Span]` objects as args so it can be used for spans filter or ents filter * Implement future entity ruler as span ruler Implement a compatible `entity_ruler` as `future_entity_ruler` using `SpanRuler` as the underlying component: * Add `sort_key` and `sort_reverse` to allow the sorting behavior to be customized. (Necessary for the same sorting/filtering as in `EntityRuler`.) * Implement `overwrite_overlapping_ents_filter` and `preserve_existing_ents_filter` to support `EntityRuler.overwrite_ents` settings. * Add `remove_by_id` to support `EntityRuler.remove` functionality. * Refactor `entity_ruler` tests to parametrize all tests to test both `entity_ruler` and `future_entity_ruler` * Implement `SpanRuler.token_patterns` and `SpanRuler.phrase_patterns` properties. Additional changes: * Move all config settings to top-level attributes to avoid duplicating settings in the config vs. `span_ruler/cfg`. (Also avoids a lot of casting.) * Format * Fix filter make method name * Refactor to use same error for removing by label or ID * Also provide existing spans to spans filter * Support ids property * Remove token_patterns and phrase_patterns * Update docstrings * Add span ruler docs * Fix types * Apply suggestions from code review Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Move sorting into filters * Check for all tokens in seen tokens in entity ruler filters * Remove registered sort key * Set Token.ent_id in a backwards-compatible way in Doc.set_ents * Remove sort options from API docs * Update docstrings * Rename entity ruler filters * Fix and parameterize scoring * Add id to Span API docs * Fix typo in API docs * Include explicit labeled=True for scorer Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
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if isinstance(span_id, str):
span_id = doc.vocab.strings.add(span_id)
if label not in doc.vocab.strings:
raise ValueError(Errors.E084.format(label=label))
start_char = doc[start].idx if start < doc.length else len(doc.text)
if start == end:
end_char = start_char
else:
end_char = doc[end - 1].idx + len(doc[end - 1])
self.c = SpanC(
label=label,
kb_id=kb_id,
Add SpanRuler component (#9880) * Add SpanRuler component Add a `SpanRuler` component similar to `EntityRuler` that saves a list of matched spans to `Doc.spans[spans_key]`. The matches from the token and phrase matchers are deduplicated and sorted before assignment but are not otherwise filtered. * Update spacy/pipeline/span_ruler.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Fix cast * Add self.key property * Use number of patterns as length * Remove patterns kwarg from init * Update spacy/tests/pipeline/test_span_ruler.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Add options for spans filter and setting to ents * Add `spans_filter` option as a registered function' * Make `spans_key` optional and if `None`, set to `doc.ents` instead of `doc.spans[spans_key]`. * Update and generalize tests * Add test for setting doc.ents, fix key property type * Fix typing * Allow independent doc.spans and doc.ents * If `spans_key` is set, set `doc.spans` with `spans_filter`. * If `annotate_ents` is set, set `doc.ents` with `ents_fitler`. * Use `util.filter_spans` by default as `ents_filter`. * Use a custom warning if the filter does not work for `doc.ents`. * Enable use of SpanC.id in Span * Support id in SpanRuler as Span.id * Update types * `id` can only be provided as string (already by `PatternType` definition) * Update all uses of Span.id/ent_id in Doc * Rename Span id kwarg to span_id * Update types and docs * Add ents filter to mimic EntityRuler overwrite_ents * Refactor `ents_filter` to take `entities, spans` args for more filtering options * Give registered filters more descriptive names * Allow registered `filter_spans` filter (`spacy.first_longest_spans_filter.v1`) to take any number of `Iterable[Span]` objects as args so it can be used for spans filter or ents filter * Implement future entity ruler as span ruler Implement a compatible `entity_ruler` as `future_entity_ruler` using `SpanRuler` as the underlying component: * Add `sort_key` and `sort_reverse` to allow the sorting behavior to be customized. (Necessary for the same sorting/filtering as in `EntityRuler`.) * Implement `overwrite_overlapping_ents_filter` and `preserve_existing_ents_filter` to support `EntityRuler.overwrite_ents` settings. * Add `remove_by_id` to support `EntityRuler.remove` functionality. * Refactor `entity_ruler` tests to parametrize all tests to test both `entity_ruler` and `future_entity_ruler` * Implement `SpanRuler.token_patterns` and `SpanRuler.phrase_patterns` properties. Additional changes: * Move all config settings to top-level attributes to avoid duplicating settings in the config vs. `span_ruler/cfg`. (Also avoids a lot of casting.) * Format * Fix filter make method name * Refactor to use same error for removing by label or ID * Also provide existing spans to spans filter * Support ids property * Remove token_patterns and phrase_patterns * Update docstrings * Add span ruler docs * Fix types * Apply suggestions from code review Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Move sorting into filters * Check for all tokens in seen tokens in entity ruler filters * Remove registered sort key * Set Token.ent_id in a backwards-compatible way in Doc.set_ents * Remove sort options from API docs * Update docstrings * Rename entity ruler filters * Fix and parameterize scoring * Add id to Span API docs * Fix typo in API docs * Include explicit labeled=True for scorer Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
2022-06-02 14:12:53 +03:00
id=span_id,
start=start,
end=end,
start_char=start_char,
end_char=end_char,
)
self._vector = vector
self._vector_norm = vector_norm
def __richcmp__(self, object other, int op):
if other is None:
if op == 0 or op == 1 or op == 2:
return False
else:
return True
if not isinstance(other, Span):
return False
cdef Span other_span = other
Add SpanRuler component (#9880) * Add SpanRuler component Add a `SpanRuler` component similar to `EntityRuler` that saves a list of matched spans to `Doc.spans[spans_key]`. The matches from the token and phrase matchers are deduplicated and sorted before assignment but are not otherwise filtered. * Update spacy/pipeline/span_ruler.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Fix cast * Add self.key property * Use number of patterns as length * Remove patterns kwarg from init * Update spacy/tests/pipeline/test_span_ruler.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Add options for spans filter and setting to ents * Add `spans_filter` option as a registered function' * Make `spans_key` optional and if `None`, set to `doc.ents` instead of `doc.spans[spans_key]`. * Update and generalize tests * Add test for setting doc.ents, fix key property type * Fix typing * Allow independent doc.spans and doc.ents * If `spans_key` is set, set `doc.spans` with `spans_filter`. * If `annotate_ents` is set, set `doc.ents` with `ents_fitler`. * Use `util.filter_spans` by default as `ents_filter`. * Use a custom warning if the filter does not work for `doc.ents`. * Enable use of SpanC.id in Span * Support id in SpanRuler as Span.id * Update types * `id` can only be provided as string (already by `PatternType` definition) * Update all uses of Span.id/ent_id in Doc * Rename Span id kwarg to span_id * Update types and docs * Add ents filter to mimic EntityRuler overwrite_ents * Refactor `ents_filter` to take `entities, spans` args for more filtering options * Give registered filters more descriptive names * Allow registered `filter_spans` filter (`spacy.first_longest_spans_filter.v1`) to take any number of `Iterable[Span]` objects as args so it can be used for spans filter or ents filter * Implement future entity ruler as span ruler Implement a compatible `entity_ruler` as `future_entity_ruler` using `SpanRuler` as the underlying component: * Add `sort_key` and `sort_reverse` to allow the sorting behavior to be customized. (Necessary for the same sorting/filtering as in `EntityRuler`.) * Implement `overwrite_overlapping_ents_filter` and `preserve_existing_ents_filter` to support `EntityRuler.overwrite_ents` settings. * Add `remove_by_id` to support `EntityRuler.remove` functionality. * Refactor `entity_ruler` tests to parametrize all tests to test both `entity_ruler` and `future_entity_ruler` * Implement `SpanRuler.token_patterns` and `SpanRuler.phrase_patterns` properties. Additional changes: * Move all config settings to top-level attributes to avoid duplicating settings in the config vs. `span_ruler/cfg`. (Also avoids a lot of casting.) * Format * Fix filter make method name * Refactor to use same error for removing by label or ID * Also provide existing spans to spans filter * Support ids property * Remove token_patterns and phrase_patterns * Update docstrings * Add span ruler docs * Fix types * Apply suggestions from code review Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Move sorting into filters * Check for all tokens in seen tokens in entity ruler filters * Remove registered sort key * Set Token.ent_id in a backwards-compatible way in Doc.set_ents * Remove sort options from API docs * Update docstrings * Rename entity ruler filters * Fix and parameterize scoring * Add id to Span API docs * Fix typo in API docs * Include explicit labeled=True for scorer Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
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self_tuple = (self.c.start_char, self.c.end_char, self.c.label, self.c.kb_id, self.id, self.doc)
other_tuple = (other_span.c.start_char, other_span.c.end_char, other_span.c.label, other_span.c.kb_id, other_span.id, other_span.doc)
# <
if op == 0:
return self_tuple < other_tuple
# <=
elif op == 1:
return self_tuple <= other_tuple
# ==
elif op == 2:
return self_tuple == other_tuple
# !=
elif op == 3:
return self_tuple != other_tuple
# >
elif op == 4:
return self_tuple > other_tuple
# >=
elif op == 5:
return self_tuple >= other_tuple
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def __hash__(self):
Add SpanRuler component (#9880) * Add SpanRuler component Add a `SpanRuler` component similar to `EntityRuler` that saves a list of matched spans to `Doc.spans[spans_key]`. The matches from the token and phrase matchers are deduplicated and sorted before assignment but are not otherwise filtered. * Update spacy/pipeline/span_ruler.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Fix cast * Add self.key property * Use number of patterns as length * Remove patterns kwarg from init * Update spacy/tests/pipeline/test_span_ruler.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Add options for spans filter and setting to ents * Add `spans_filter` option as a registered function' * Make `spans_key` optional and if `None`, set to `doc.ents` instead of `doc.spans[spans_key]`. * Update and generalize tests * Add test for setting doc.ents, fix key property type * Fix typing * Allow independent doc.spans and doc.ents * If `spans_key` is set, set `doc.spans` with `spans_filter`. * If `annotate_ents` is set, set `doc.ents` with `ents_fitler`. * Use `util.filter_spans` by default as `ents_filter`. * Use a custom warning if the filter does not work for `doc.ents`. * Enable use of SpanC.id in Span * Support id in SpanRuler as Span.id * Update types * `id` can only be provided as string (already by `PatternType` definition) * Update all uses of Span.id/ent_id in Doc * Rename Span id kwarg to span_id * Update types and docs * Add ents filter to mimic EntityRuler overwrite_ents * Refactor `ents_filter` to take `entities, spans` args for more filtering options * Give registered filters more descriptive names * Allow registered `filter_spans` filter (`spacy.first_longest_spans_filter.v1`) to take any number of `Iterable[Span]` objects as args so it can be used for spans filter or ents filter * Implement future entity ruler as span ruler Implement a compatible `entity_ruler` as `future_entity_ruler` using `SpanRuler` as the underlying component: * Add `sort_key` and `sort_reverse` to allow the sorting behavior to be customized. (Necessary for the same sorting/filtering as in `EntityRuler`.) * Implement `overwrite_overlapping_ents_filter` and `preserve_existing_ents_filter` to support `EntityRuler.overwrite_ents` settings. * Add `remove_by_id` to support `EntityRuler.remove` functionality. * Refactor `entity_ruler` tests to parametrize all tests to test both `entity_ruler` and `future_entity_ruler` * Implement `SpanRuler.token_patterns` and `SpanRuler.phrase_patterns` properties. Additional changes: * Move all config settings to top-level attributes to avoid duplicating settings in the config vs. `span_ruler/cfg`. (Also avoids a lot of casting.) * Format * Fix filter make method name * Refactor to use same error for removing by label or ID * Also provide existing spans to spans filter * Support ids property * Remove token_patterns and phrase_patterns * Update docstrings * Add span ruler docs * Fix types * Apply suggestions from code review Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Move sorting into filters * Check for all tokens in seen tokens in entity ruler filters * Remove registered sort key * Set Token.ent_id in a backwards-compatible way in Doc.set_ents * Remove sort options from API docs * Update docstrings * Rename entity ruler filters * Fix and parameterize scoring * Add id to Span API docs * Fix typo in API docs * Include explicit labeled=True for scorer Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
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return hash((self.doc, self.c.start_char, self.c.end_char, self.c.label, self.c.kb_id, self.c.id))
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def __len__(self):
"""Get the number of tokens in the span.
RETURNS (int): The number of tokens in the span.
DOCS: https://spacy.io/api/span#len
"""
if self.c.end < self.c.start:
return 0
return self.c.end - self.c.start
def __repr__(self):
return self.text
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def __getitem__(self, object i):
"""Get a `Token` or a `Span` object
i (int or tuple): The index of the token within the span, or slice of
the span to get.
RETURNS (Token or Span): The token at `span[i]`.
DOCS: https://spacy.io/api/span#getitem
"""
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if isinstance(i, slice):
start, end = normalize_slice(len(self), i.start, i.stop, i.step)
return Span(self.doc, start + self.start, end + self.start)
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else:
if i < 0:
token_i = self.c.end + i
else:
token_i = self.c.start + i
if self.c.start <= token_i < self.c.end:
return self.doc[token_i]
else:
Add AttributeRuler for token attribute exceptions (#5842) * Add AttributeRuler for token attribute exceptions Add the `AttributeRuler` to handle exceptions for token-level attributes. The `AttributeRuler` uses `Matcher` patterns to identify target spans and applies the specified attributes to the token at the provided index in the matched span. A negative index can be used to index from the end of the matched span. The retokenizer is used to "merge" the individual tokens and assign them the provided attributes. Helper functions can import existing tag maps and morph rules to the corresponding `Matcher` patterns. There is an additional minor bug fix for `MORPH` attributes in the retokenizer to correctly normalize the values and to handle `MORPH` alongside `_` in an attrs dict. * Fix default name * Update name in error message * Extend AttributeRuler functionality * Add option to initialize with a dict of AttributeRuler patterns * Instead of silently discarding overlapping matches (the default behavior for the retokenizer if only the attrs differ), split the matches into disjoint sets and retokenize each set separately. This allows, for instance, one pattern to set the POS and another pattern to set the lemma. (If two matches modify the same attribute, it looks like the attrs are applied in the order they were added, but it may not be deterministic?) * Improve types * Sort spans before processing * Fix index boundaries in Span * Refactor retokenizer to separate attrs methods Add top-level `normalize_token_attrs` and `set_token_attrs` methods. * Update AttributeRuler to use refactored methods Update `AttributeRuler` to replace use of full retokenizer with only the relevant methods for normalizing and setting attributes for a single token. * Update spacy/pipeline/attributeruler.py Co-authored-by: Ines Montani <ines@ines.io> * Make API more similar to EntityRuler * Add `AttributeRuler.add_patterns` to add patterns from a list of dicts * Return list of dicts as property `AttributeRuler.patterns` * Make attrs_unnormed private * Add test loading patterns from assets * Revert "Fix index boundaries in Span" This reverts commit 8f8a5c33861bff2d7c3f19914e289139ab3a2c28. * Add Span index boundary checks (#5861) * Add Span index boundary checks * Return Span-specific IndexError in all cases * Simplify and fix if/else Co-authored-by: Ines Montani <ines@ines.io>
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raise IndexError(Errors.E1002)
def __iter__(self):
"""Iterate over `Token` objects.
YIELDS (Token): A `Token` object.
DOCS: https://spacy.io/api/span#iter
"""
for i in range(self.c.start, self.c.end):
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yield self.doc[i]
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def __reduce__(self):
raise NotImplementedError(Errors.E112)
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@property
def _(self):
"""Custom extension attributes registered via `set_extension`."""
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return Underscore(Underscore.span_extensions, self,
start=self.c.start_char, end=self.c.end_char)
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def as_doc(self, *, bint copy_user_data=False, array_head=None, array=None):
"""Create a `Doc` object with a copy of the `Span`'s data.
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copy_user_data (bool): Whether or not to copy the original doc's user data.
array_head (tuple): `Doc` array attrs, can be passed in to speed up computation.
array (ndarray): `Doc` as array, can be passed in to speed up computation.
RETURNS (Doc): The `Doc` copy of the span.
DOCS: https://spacy.io/api/span#as_doc
"""
words = [t.text for t in self]
spaces = [bool(t.whitespace_) for t in self]
cdef Doc doc = Doc(self.doc.vocab, words=words, spaces=spaces)
if array_head is None:
array_head = self.doc._get_array_attrs()
if array is None:
array = self.doc.to_array(array_head)
array = array[self.start : self.end]
self._fix_dep_copy(array_head, array)
# Fix initial IOB so the entities are valid for doc.ents below.
if len(array) > 0 and ENT_IOB in array_head:
ent_iob_col = array_head.index(ENT_IOB)
if array[0][ent_iob_col] == 1:
array[0][ent_iob_col] = 3
doc.from_array(array_head, array)
# Set partial entities at the beginning or end of the span to have
# missing entity annotation. Note: the initial partial entity could be
# detected from the IOB annotation but the final partial entity can't,
# so detect and remove both in the same way by checking self.ents.
span_ents = {(ent.start, ent.end) for ent in self.ents}
doc_ents = doc.ents
if len(doc_ents) > 0:
# Remove initial partial ent
if (doc_ents[0].start + self.start, doc_ents[0].end + self.start) not in span_ents:
doc.set_ents([], missing=[doc_ents[0]], default="unmodified")
# Remove final partial ent
if (doc_ents[-1].start + self.start, doc_ents[-1].end + self.start) not in span_ents:
doc.set_ents([], missing=[doc_ents[-1]], default="unmodified")
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doc.noun_chunks_iterator = self.doc.noun_chunks_iterator
doc.user_hooks = self.doc.user_hooks
doc.user_span_hooks = self.doc.user_span_hooks
doc.user_token_hooks = self.doc.user_token_hooks
doc.vector = self.vector
doc.vector_norm = self.vector_norm
doc.tensor = self.doc.tensor[self.start : self.end]
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for key, value in self.doc.cats.items():
if hasattr(key, "__len__") and len(key) == 3:
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cat_start, cat_end, cat_label = key
if cat_start == self.start_char and cat_end == self.end_char:
doc.cats[cat_label] = value
if copy_user_data:
user_data = {}
char_offset = self.start_char
for key, value in self.doc.user_data.items():
if isinstance(key, tuple) and len(key) == 4 and key[0] == "._.":
data_type, name, start, end = key
if start is not None or end is not None:
start -= char_offset
if end is not None:
end -= char_offset
user_data[(data_type, name, start, end)] = copy.copy(value)
else:
user_data[key] = copy.copy(value)
doc.user_data = user_data
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return doc
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def _fix_dep_copy(self, attrs, array):
""" Rewire dependency links to make sure their heads fall into the span
while still keeping the correct number of sentences. """
cdef int length = len(array)
cdef attr_t value
cdef int i, head_col, ancestor_i
old_to_new_root = dict()
if HEAD in attrs:
head_col = attrs.index(HEAD)
for i in range(length):
# if the HEAD refers to a token outside this span, find a more appropriate ancestor
token = self[i]
ancestor_i = token.head.i - self.c.start # span offset
if ancestor_i not in range(length):
if DEP in attrs:
array[i, attrs.index(DEP)] = dep
# try finding an ancestor within this span
ancestors = token.ancestors
for ancestor in ancestors:
ancestor_i = ancestor.i - self.c.start
if ancestor_i in range(length):
array[i, head_col] = numpy.int32(ancestor_i - i).astype(numpy.uint64)
# if there is no appropriate ancestor, define a new artificial root
value = array[i, head_col]
if (i+value) not in range(length):
new_root = old_to_new_root.get(ancestor_i, None)
if new_root is not None:
# take the same artificial root as a previous token from the same sentence
array[i, head_col] = numpy.int32(new_root - i).astype(numpy.uint64)
else:
# set this token as the new artificial root
array[i, head_col] = 0
old_to_new_root[ancestor_i] = i
return array
def get_lca_matrix(self):
"""Calculates a matrix of Lowest Common Ancestors (LCA) for a given
`Span`, where LCA[i, j] is the index of the lowest common ancestor among
the tokens span[i] and span[j]. If they have no common ancestor within
the span, LCA[i, j] will be -1.
RETURNS (np.array[ndim=2, dtype=numpy.int32]): LCA matrix with shape
(n, n), where n = len(self).
DOCS: https://spacy.io/api/span#get_lca_matrix
"""
return numpy.asarray(_get_lca_matrix(self.doc, self.c.start, self.c.end))
def similarity(self, other):
"""Make a semantic similarity estimate. The default estimate is cosine
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similarity using an average of word vectors.
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other (object): The object to compare with. By default, accepts `Doc`,
`Span`, `Token` and `Lexeme` objects.
RETURNS (float): A scalar similarity score. Higher is more similar.
DOCS: https://spacy.io/api/span#similarity
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"""
if "similarity" in self.doc.user_span_hooks:
return self.doc.user_span_hooks["similarity"](self, other)
attr = getattr(self.doc.vocab.vectors, "attr", ORTH)
cdef Token this_token
cdef Token other_token
cdef Lexeme other_lex
if len(self) == 1 and isinstance(other, Token):
this_token = self[0]
other_token = other
if Token.get_struct_attr(this_token.c, attr) == Token.get_struct_attr(other_token.c, attr):
return 1.0
elif len(self) == 1 and isinstance(other, Lexeme):
this_token = self[0]
other_lex = other
if Token.get_struct_attr(this_token.c, attr) == Lexeme.get_struct_attr(other_lex.c, attr):
return 1.0
elif isinstance(other, (Doc, Span)) and len(self) == len(other):
similar = True
for i in range(len(self)):
this_token = self[i]
other_token = other[i]
if Token.get_struct_attr(this_token.c, attr) != Token.get_struct_attr(other_token.c, attr):
similar = False
break
if similar:
return 1.0
if self.vocab.vectors.n_keys == 0:
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warnings.warn(Warnings.W007.format(obj="Span"))
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if self.vector_norm == 0.0 or other.vector_norm == 0.0:
if not self.has_vector or not other.has_vector:
warnings.warn(Warnings.W008.format(obj="Span"))
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return 0.0
vector = self.vector
xp = get_array_module(vector)
result = xp.dot(vector, other.vector) / (self.vector_norm * other.vector_norm)
# ensure we get a scalar back (numpy does this automatically but cupy doesn't)
return result.item()
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cpdef np.ndarray to_array(self, object py_attr_ids):
"""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.
attr_ids (list[int]): A list of attribute ID ints.
RETURNS (numpy.ndarray[long, ndim=2]): A feature matrix, with one row
per word, and one column per attribute indicated in the input
`attr_ids`.
"""
cdef int i, j
cdef attr_id_t feature
cdef np.ndarray[attr_t, ndim=2] output
# Make an array from the attributes - otherwise our inner loop is Python
# dict iteration
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cdef np.ndarray[attr_t, ndim=1] attr_ids = numpy.asarray(py_attr_ids, dtype=numpy.uint64)
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cdef int length = self.end - self.start
output = numpy.ndarray(shape=(length, len(attr_ids)), dtype=numpy.uint64)
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for i in range(self.start, self.end):
for j, feature in enumerate(attr_ids):
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output[i-self.start, j] = get_token_attr(&self.doc.c[i], feature)
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return output
@property
def vocab(self):
"""RETURNS (Vocab): The Span's Doc's vocab."""
return self.doc.vocab
@property
def sent(self):
"""Obtain the sentence that contains this span. If the given span
crosses sentence boundaries, return only the first sentence
to which it belongs.
RETURNS (Span): The sentence span that the span is a part of.
"""
if "sent" in self.doc.user_span_hooks:
return self.doc.user_span_hooks["sent"](self)
elif "sents" in self.doc.user_hooks:
for sentence in self.doc.user_hooks["sents"](self.doc):
if sentence.start <= self.start < sentence.end:
return sentence
# Use `sent_start` token attribute to find sentence boundaries
cdef int n = 0
if self.doc.has_annotation("SENT_START"):
# Find start of the sentence
start = self.start
while self.doc.c[start].sent_start != 1 and start > 0:
start += -1
# Find end of the sentence - can be within the entity
end = self.start + 1
while end < self.doc.length and self.doc.c[end].sent_start != 1:
end += 1
n += 1
if n >= self.doc.length:
break
return self.doc[start:end]
else:
raise ValueError(Errors.E030)
@property
def sents(self):
"""Obtain the sentences that contain this span. If the given span
crosses sentence boundaries, return all sentences it is a part of.
RETURNS (Iterable[Span]): All sentences that the span is a part of.
DOCS: https://spacy.io/api/span#sents
"""
cdef int start
cdef int i
if "sents" in self.doc.user_span_hooks:
yield from self.doc.user_span_hooks["sents"](self)
elif "sents" in self.doc.user_hooks:
for sentence in self.doc.user_hooks["sents"](self.doc):
if sentence.end > self.start:
if sentence.start < self.end or sentence.start == self.start == self.end:
yield sentence
else:
break
else:
if not self.doc.has_annotation("SENT_START"):
raise ValueError(Errors.E030)
# Use `sent_start` token attribute to find sentence boundaries
# Find start of the 1st sentence of the Span
start = self.start
while self.doc.c[start].sent_start != 1 and start > 0:
start -= 1
# Now, find all the sentences in the span
for i in range(start + 1, self.doc.length):
if self.doc.c[i].sent_start == 1:
yield Span(self.doc, start, i)
start = i
if start >= self.end:
break
elif i == self.doc.length - 1:
yield Span(self.doc, start, self.doc.length)
# Ensure that trailing parts of the Span instance are included in last element of .sents.
if start == self.doc.length - 1:
yield Span(self.doc, start, self.doc.length)
@property
def ents(self):
"""The named entities that fall completely within the span. Returns
a tuple of `Span` objects.
RETURNS (tuple): Entities in the span, one `Span` per entity.
DOCS: https://spacy.io/api/span#ents
"""
cdef Span ent
ents = []
for ent in self.doc.ents:
if ent.c.start >= self.c.start:
if ent.c.end <= self.c.end:
ents.append(ent)
else:
break
return ents
@property
def has_vector(self):
"""A boolean value indicating whether a word vector is associated with
the object.
RETURNS (bool): Whether a word vector is associated with the object.
DOCS: https://spacy.io/api/span#has_vector
"""
if "has_vector" in self.doc.user_span_hooks:
return self.doc.user_span_hooks["has_vector"](self)
elif self.vocab.vectors.size > 0:
return any(token.has_vector for token in self)
elif self.doc.tensor.size > 0:
return True
else:
return False
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@property
def vector(self):
"""A real-valued meaning representation. Defaults to an average of the
token vectors.
RETURNS (numpy.ndarray[ndim=1, dtype='float32']): A 1D numpy array
representing the span's semantics.
DOCS: https://spacy.io/api/span#vector
"""
if "vector" in self.doc.user_span_hooks:
return self.doc.user_span_hooks["vector"](self)
if self._vector is None:
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if not len(self):
xp = get_array_module(self.vocab.vectors.data)
self._vector = xp.zeros((self.vocab.vectors_length,), dtype="f")
else:
self._vector = sum(t.vector for t in self) / len(self)
return self._vector
@property
def vector_norm(self):
"""The L2 norm of the span's vector representation.
RETURNS (float): The L2 norm of the vector representation.
DOCS: https://spacy.io/api/span#vector_norm
"""
if "vector_norm" in self.doc.user_span_hooks:
return self.doc.user_span_hooks["vector"](self)
if self._vector_norm is None:
vector = self.vector
total = (vector*vector).sum()
xp = get_array_module(vector)
self._vector_norm = xp.sqrt(total) if total != 0. else 0.
return self._vector_norm
@property
def tensor(self):
"""The span's slice of the doc's tensor.
RETURNS (ndarray[ndim=2, dtype='float32']): A 2D numpy or cupy array
representing the span's semantics.
"""
if self.doc.tensor is None:
return None
return self.doc.tensor[self.start : self.end]
@property
def sentiment(self):
"""RETURNS (float): A scalar value indicating the positivity or
negativity of the span.
"""
if "sentiment" in self.doc.user_span_hooks:
return self.doc.user_span_hooks["sentiment"](self)
else:
return sum([token.sentiment for token in self]) / len(self)
@property
def text(self):
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"""RETURNS (str): The original verbatim text of the span."""
text = self.text_with_ws
if len(self) > 0 and self[-1].whitespace_:
text = text[:-1]
return text
@property
def text_with_ws(self):
"""The text content of the span with a trailing whitespace character if
the last token has one.
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RETURNS (str): The text content of the span (with trailing
whitespace).
"""
return "".join([t.text_with_ws for t in self])
@property
def noun_chunks(self):
"""Iterate over the base noun phrases in the span. Yields base
noun-phrase #[code Span] objects, if the language has a noun chunk iterator.
Raises a NotImplementedError otherwise.
A base noun phrase, or "NP chunk", is a noun
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phrase that does not permit other NPs to be nested within it so no
NP-level coordination, no prepositional phrases, and no relative
clauses.
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YIELDS (Span): Noun chunks in the span.
DOCS: https://spacy.io/api/span#noun_chunks
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"""
for span in self.doc.noun_chunks:
if span.start >= self.start and span.end <= self.end:
yield span
@property
def root(self):
"""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.
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RETURNS (Token): The root token.
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DOCS: https://spacy.io/api/span#root
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"""
if "root" in self.doc.user_span_hooks:
return self.doc.user_span_hooks["root"](self)
# This should probably be called 'head', and the other one called
# 'gov'. But we went with 'head' elsewhere, and now we're stuck =/
cdef int i
# First, we scan through the Span, and check whether there's a word
# with head==0, i.e. a sentence root. If so, we can return it. The
# longer the span, the more likely it contains a sentence root, and
# in this case we return in linear time.
for i in range(self.c.start, self.c.end):
if self.doc.c[i].head == 0:
return self.doc[i]
# If we don't have a sentence root, we do something that's not so
# algorithmically clever, but I think should be quite fast,
# especially for short spans.
# For each word, we count the path length, and arg min this measure.
# We could use better tree logic to save steps here...But I
# think this should be okay.
cdef int current_best = self.doc.length
cdef int root = -1
for i in range(self.c.start, self.c.end):
if self.c.start <= (i+self.doc.c[i].head) < self.c.end:
continue
words_to_root = _count_words_to_root(&self.doc.c[i], self.doc.length)
if words_to_root < current_best:
current_best = words_to_root
root = i
if root == -1:
return self.doc[self.c.start]
else:
return self.doc[root]
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def char_span(self, int start_idx, int end_idx, label=0, kb_id=0, vector=None, id=0, alignment_mode="strict", span_id=0):
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"""Create a `Span` object from the slice `span.text[start : end]`.
start (int): The index of the first character of the span.
end (int): The index of the first character after the span.
label (Union[int, str]): A label to attach to the Span, e.g. for
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named entities.
kb_id (Union[int, str]): An ID from a KB to capture the meaning of a named entity.
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vector (ndarray[ndim=1, dtype='float32']): A meaning representation of
the span.
id (Union[int, str]): Unused.
alignment_mode (str): How character indices are aligned to token
boundaries. Options: "strict" (character indices must be aligned
with token boundaries), "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".
span_id (Union[int, str]): An identifier to associate with the span.
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RETURNS (Span): The newly constructed object.
"""
start_idx += self.c.start_char
end_idx += self.c.start_char
return self.doc.char_span(start_idx, end_idx, label=label, kb_id=kb_id, vector=vector, alignment_mode=alignment_mode, span_id=span_id)
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@property
def conjuncts(self):
"""Tokens that are conjoined to the span's root.
RETURNS (tuple): A tuple of Token objects.
DOCS: https://spacy.io/api/span#lefts
"""
return self.root.conjuncts
@property
def lefts(self):
"""Tokens that are to the left of the span, whose head is within the
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`Span`.
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YIELDS (Token):A left-child of a token of the span.
DOCS: https://spacy.io/api/span#lefts
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"""
for token in reversed(self): # Reverse, so we get tokens in order
for left in token.lefts:
if left.i < self.start:
yield left
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@property
def rights(self):
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"""Tokens that are to the right of the Span, whose head is within the
`Span`.
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YIELDS (Token): A right-child of a token of the span.
DOCS: https://spacy.io/api/span#rights
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"""
for token in self:
for right in token.rights:
if right.i >= self.end:
yield right
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@property
def n_lefts(self):
"""The number of tokens that are to the left of the span, whose
heads are within the span.
RETURNS (int): The number of leftward immediate children of the
span, in the syntactic dependency parse.
DOCS: https://spacy.io/api/span#n_lefts
"""
return len(list(self.lefts))
@property
def n_rights(self):
"""The number of tokens that are to the right of the span, whose
heads are within the span.
RETURNS (int): The number of rightward immediate children of the
span, in the syntactic dependency parse.
DOCS: https://spacy.io/api/span#n_rights
"""
return len(list(self.rights))
@property
def subtree(self):
"""Tokens within the span and tokens which descend from them.
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YIELDS (Token): A token within the span, or a descendant from it.
DOCS: https://spacy.io/api/span#subtree
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"""
for word in self.lefts:
yield from word.subtree
yield from self
for word in self.rights:
yield from word.subtree
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@property
def start(self):
return self.c.start
@start.setter
def start(self, int start):
if start < 0:
raise IndexError(Errors.E1032.format(var="start", forbidden="< 0", value=start))
self.c.start = start
@property
def end(self):
return self.c.end
@end.setter
def end(self, int end):
if end < 0:
raise IndexError(Errors.E1032.format(var="end", forbidden="< 0", value=end))
self.c.end = end
@property
def start_char(self):
return self.c.start_char
@start_char.setter
def start_char(self, int start_char):
if start_char < 0:
raise IndexError(Errors.E1032.format(var="start_char", forbidden="< 0", value=start_char))
self.c.start_char = start_char
@property
def end_char(self):
return self.c.end_char
@end_char.setter
def end_char(self, int end_char):
if end_char < 0:
raise IndexError(Errors.E1032.format(var="end_char", forbidden="< 0", value=end_char))
self.c.end_char = end_char
@property
def label(self):
return self.c.label
@label.setter
def label(self, attr_t label):
self.c.label = label
@property
def kb_id(self):
return self.c.kb_id
@kb_id.setter
def kb_id(self, attr_t kb_id):
self.c.kb_id = kb_id
@property
def id(self):
return self.c.id
Add SpanRuler component (#9880) * Add SpanRuler component Add a `SpanRuler` component similar to `EntityRuler` that saves a list of matched spans to `Doc.spans[spans_key]`. The matches from the token and phrase matchers are deduplicated and sorted before assignment but are not otherwise filtered. * Update spacy/pipeline/span_ruler.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Fix cast * Add self.key property * Use number of patterns as length * Remove patterns kwarg from init * Update spacy/tests/pipeline/test_span_ruler.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Add options for spans filter and setting to ents * Add `spans_filter` option as a registered function' * Make `spans_key` optional and if `None`, set to `doc.ents` instead of `doc.spans[spans_key]`. * Update and generalize tests * Add test for setting doc.ents, fix key property type * Fix typing * Allow independent doc.spans and doc.ents * If `spans_key` is set, set `doc.spans` with `spans_filter`. * If `annotate_ents` is set, set `doc.ents` with `ents_fitler`. * Use `util.filter_spans` by default as `ents_filter`. * Use a custom warning if the filter does not work for `doc.ents`. * Enable use of SpanC.id in Span * Support id in SpanRuler as Span.id * Update types * `id` can only be provided as string (already by `PatternType` definition) * Update all uses of Span.id/ent_id in Doc * Rename Span id kwarg to span_id * Update types and docs * Add ents filter to mimic EntityRuler overwrite_ents * Refactor `ents_filter` to take `entities, spans` args for more filtering options * Give registered filters more descriptive names * Allow registered `filter_spans` filter (`spacy.first_longest_spans_filter.v1`) to take any number of `Iterable[Span]` objects as args so it can be used for spans filter or ents filter * Implement future entity ruler as span ruler Implement a compatible `entity_ruler` as `future_entity_ruler` using `SpanRuler` as the underlying component: * Add `sort_key` and `sort_reverse` to allow the sorting behavior to be customized. (Necessary for the same sorting/filtering as in `EntityRuler`.) * Implement `overwrite_overlapping_ents_filter` and `preserve_existing_ents_filter` to support `EntityRuler.overwrite_ents` settings. * Add `remove_by_id` to support `EntityRuler.remove` functionality. * Refactor `entity_ruler` tests to parametrize all tests to test both `entity_ruler` and `future_entity_ruler` * Implement `SpanRuler.token_patterns` and `SpanRuler.phrase_patterns` properties. Additional changes: * Move all config settings to top-level attributes to avoid duplicating settings in the config vs. `span_ruler/cfg`. (Also avoids a lot of casting.) * Format * Fix filter make method name * Refactor to use same error for removing by label or ID * Also provide existing spans to spans filter * Support ids property * Remove token_patterns and phrase_patterns * Update docstrings * Add span ruler docs * Fix types * Apply suggestions from code review Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Move sorting into filters * Check for all tokens in seen tokens in entity ruler filters * Remove registered sort key * Set Token.ent_id in a backwards-compatible way in Doc.set_ents * Remove sort options from API docs * Update docstrings * Rename entity ruler filters * Fix and parameterize scoring * Add id to Span API docs * Fix typo in API docs * Include explicit labeled=True for scorer Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
2022-06-02 14:12:53 +03:00
@id.setter
def id(self, attr_t id):
self.c.id = id
Add SpanRuler component (#9880) * Add SpanRuler component Add a `SpanRuler` component similar to `EntityRuler` that saves a list of matched spans to `Doc.spans[spans_key]`. The matches from the token and phrase matchers are deduplicated and sorted before assignment but are not otherwise filtered. * Update spacy/pipeline/span_ruler.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Fix cast * Add self.key property * Use number of patterns as length * Remove patterns kwarg from init * Update spacy/tests/pipeline/test_span_ruler.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Add options for spans filter and setting to ents * Add `spans_filter` option as a registered function' * Make `spans_key` optional and if `None`, set to `doc.ents` instead of `doc.spans[spans_key]`. * Update and generalize tests * Add test for setting doc.ents, fix key property type * Fix typing * Allow independent doc.spans and doc.ents * If `spans_key` is set, set `doc.spans` with `spans_filter`. * If `annotate_ents` is set, set `doc.ents` with `ents_fitler`. * Use `util.filter_spans` by default as `ents_filter`. * Use a custom warning if the filter does not work for `doc.ents`. * Enable use of SpanC.id in Span * Support id in SpanRuler as Span.id * Update types * `id` can only be provided as string (already by `PatternType` definition) * Update all uses of Span.id/ent_id in Doc * Rename Span id kwarg to span_id * Update types and docs * Add ents filter to mimic EntityRuler overwrite_ents * Refactor `ents_filter` to take `entities, spans` args for more filtering options * Give registered filters more descriptive names * Allow registered `filter_spans` filter (`spacy.first_longest_spans_filter.v1`) to take any number of `Iterable[Span]` objects as args so it can be used for spans filter or ents filter * Implement future entity ruler as span ruler Implement a compatible `entity_ruler` as `future_entity_ruler` using `SpanRuler` as the underlying component: * Add `sort_key` and `sort_reverse` to allow the sorting behavior to be customized. (Necessary for the same sorting/filtering as in `EntityRuler`.) * Implement `overwrite_overlapping_ents_filter` and `preserve_existing_ents_filter` to support `EntityRuler.overwrite_ents` settings. * Add `remove_by_id` to support `EntityRuler.remove` functionality. * Refactor `entity_ruler` tests to parametrize all tests to test both `entity_ruler` and `future_entity_ruler` * Implement `SpanRuler.token_patterns` and `SpanRuler.phrase_patterns` properties. Additional changes: * Move all config settings to top-level attributes to avoid duplicating settings in the config vs. `span_ruler/cfg`. (Also avoids a lot of casting.) * Format * Fix filter make method name * Refactor to use same error for removing by label or ID * Also provide existing spans to spans filter * Support ids property * Remove token_patterns and phrase_patterns * Update docstrings * Add span ruler docs * Fix types * Apply suggestions from code review Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Move sorting into filters * Check for all tokens in seen tokens in entity ruler filters * Remove registered sort key * Set Token.ent_id in a backwards-compatible way in Doc.set_ents * Remove sort options from API docs * Update docstrings * Rename entity ruler filters * Fix and parameterize scoring * Add id to Span API docs * Fix typo in API docs * Include explicit labeled=True for scorer Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
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@property
def ent_id(self):
"""RETURNS (uint64): The entity ID."""
return self.root.ent_id
@ent_id.setter
def ent_id(self, hash_t key):
raise NotImplementedError(Errors.E200.format(attr="ent_id"))
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@property
def ent_id_(self):
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"""RETURNS (str): The (string) entity ID."""
return self.root.ent_id_
@ent_id_.setter
def ent_id_(self, str key):
raise NotImplementedError(Errors.E200.format(attr="ent_id_"))
@property
def orth_(self):
"""Verbatim text content (identical to `Span.text`). Exists mostly for
consistency with other attributes.
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RETURNS (str): The span's text."""
return self.text
@property
def lemma_(self):
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"""RETURNS (str): The span's lemma."""
return "".join([t.lemma_ + t.whitespace_ for t in self]).strip()
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@property
def label_(self):
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"""RETURNS (str): The span's label."""
return self.doc.vocab.strings[self.label]
@label_.setter
def label_(self, str label_):
self.label = self.doc.vocab.strings.add(label_)
@property
def kb_id_(self):
Add SpanRuler component (#9880) * Add SpanRuler component Add a `SpanRuler` component similar to `EntityRuler` that saves a list of matched spans to `Doc.spans[spans_key]`. The matches from the token and phrase matchers are deduplicated and sorted before assignment but are not otherwise filtered. * Update spacy/pipeline/span_ruler.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Fix cast * Add self.key property * Use number of patterns as length * Remove patterns kwarg from init * Update spacy/tests/pipeline/test_span_ruler.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Add options for spans filter and setting to ents * Add `spans_filter` option as a registered function' * Make `spans_key` optional and if `None`, set to `doc.ents` instead of `doc.spans[spans_key]`. * Update and generalize tests * Add test for setting doc.ents, fix key property type * Fix typing * Allow independent doc.spans and doc.ents * If `spans_key` is set, set `doc.spans` with `spans_filter`. * If `annotate_ents` is set, set `doc.ents` with `ents_fitler`. * Use `util.filter_spans` by default as `ents_filter`. * Use a custom warning if the filter does not work for `doc.ents`. * Enable use of SpanC.id in Span * Support id in SpanRuler as Span.id * Update types * `id` can only be provided as string (already by `PatternType` definition) * Update all uses of Span.id/ent_id in Doc * Rename Span id kwarg to span_id * Update types and docs * Add ents filter to mimic EntityRuler overwrite_ents * Refactor `ents_filter` to take `entities, spans` args for more filtering options * Give registered filters more descriptive names * Allow registered `filter_spans` filter (`spacy.first_longest_spans_filter.v1`) to take any number of `Iterable[Span]` objects as args so it can be used for spans filter or ents filter * Implement future entity ruler as span ruler Implement a compatible `entity_ruler` as `future_entity_ruler` using `SpanRuler` as the underlying component: * Add `sort_key` and `sort_reverse` to allow the sorting behavior to be customized. (Necessary for the same sorting/filtering as in `EntityRuler`.) * Implement `overwrite_overlapping_ents_filter` and `preserve_existing_ents_filter` to support `EntityRuler.overwrite_ents` settings. * Add `remove_by_id` to support `EntityRuler.remove` functionality. * Refactor `entity_ruler` tests to parametrize all tests to test both `entity_ruler` and `future_entity_ruler` * Implement `SpanRuler.token_patterns` and `SpanRuler.phrase_patterns` properties. Additional changes: * Move all config settings to top-level attributes to avoid duplicating settings in the config vs. `span_ruler/cfg`. (Also avoids a lot of casting.) * Format * Fix filter make method name * Refactor to use same error for removing by label or ID * Also provide existing spans to spans filter * Support ids property * Remove token_patterns and phrase_patterns * Update docstrings * Add span ruler docs * Fix types * Apply suggestions from code review Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Move sorting into filters * Check for all tokens in seen tokens in entity ruler filters * Remove registered sort key * Set Token.ent_id in a backwards-compatible way in Doc.set_ents * Remove sort options from API docs * Update docstrings * Rename entity ruler filters * Fix and parameterize scoring * Add id to Span API docs * Fix typo in API docs * Include explicit labeled=True for scorer Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
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"""RETURNS (str): The span's KB ID."""
return self.doc.vocab.strings[self.kb_id]
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@kb_id_.setter
def kb_id_(self, str kb_id_):
self.kb_id = self.doc.vocab.strings.add(kb_id_)
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@property
def id_(self):
Add SpanRuler component (#9880) * Add SpanRuler component Add a `SpanRuler` component similar to `EntityRuler` that saves a list of matched spans to `Doc.spans[spans_key]`. The matches from the token and phrase matchers are deduplicated and sorted before assignment but are not otherwise filtered. * Update spacy/pipeline/span_ruler.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Fix cast * Add self.key property * Use number of patterns as length * Remove patterns kwarg from init * Update spacy/tests/pipeline/test_span_ruler.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Add options for spans filter and setting to ents * Add `spans_filter` option as a registered function' * Make `spans_key` optional and if `None`, set to `doc.ents` instead of `doc.spans[spans_key]`. * Update and generalize tests * Add test for setting doc.ents, fix key property type * Fix typing * Allow independent doc.spans and doc.ents * If `spans_key` is set, set `doc.spans` with `spans_filter`. * If `annotate_ents` is set, set `doc.ents` with `ents_fitler`. * Use `util.filter_spans` by default as `ents_filter`. * Use a custom warning if the filter does not work for `doc.ents`. * Enable use of SpanC.id in Span * Support id in SpanRuler as Span.id * Update types * `id` can only be provided as string (already by `PatternType` definition) * Update all uses of Span.id/ent_id in Doc * Rename Span id kwarg to span_id * Update types and docs * Add ents filter to mimic EntityRuler overwrite_ents * Refactor `ents_filter` to take `entities, spans` args for more filtering options * Give registered filters more descriptive names * Allow registered `filter_spans` filter (`spacy.first_longest_spans_filter.v1`) to take any number of `Iterable[Span]` objects as args so it can be used for spans filter or ents filter * Implement future entity ruler as span ruler Implement a compatible `entity_ruler` as `future_entity_ruler` using `SpanRuler` as the underlying component: * Add `sort_key` and `sort_reverse` to allow the sorting behavior to be customized. (Necessary for the same sorting/filtering as in `EntityRuler`.) * Implement `overwrite_overlapping_ents_filter` and `preserve_existing_ents_filter` to support `EntityRuler.overwrite_ents` settings. * Add `remove_by_id` to support `EntityRuler.remove` functionality. * Refactor `entity_ruler` tests to parametrize all tests to test both `entity_ruler` and `future_entity_ruler` * Implement `SpanRuler.token_patterns` and `SpanRuler.phrase_patterns` properties. Additional changes: * Move all config settings to top-level attributes to avoid duplicating settings in the config vs. `span_ruler/cfg`. (Also avoids a lot of casting.) * Format * Fix filter make method name * Refactor to use same error for removing by label or ID * Also provide existing spans to spans filter * Support ids property * Remove token_patterns and phrase_patterns * Update docstrings * Add span ruler docs * Fix types * Apply suggestions from code review Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Move sorting into filters * Check for all tokens in seen tokens in entity ruler filters * Remove registered sort key * Set Token.ent_id in a backwards-compatible way in Doc.set_ents * Remove sort options from API docs * Update docstrings * Rename entity ruler filters * Fix and parameterize scoring * Add id to Span API docs * Fix typo in API docs * Include explicit labeled=True for scorer Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
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"""RETURNS (str): The span's ID."""
return self.doc.vocab.strings[self.id]
Add SpanRuler component (#9880) * Add SpanRuler component Add a `SpanRuler` component similar to `EntityRuler` that saves a list of matched spans to `Doc.spans[spans_key]`. The matches from the token and phrase matchers are deduplicated and sorted before assignment but are not otherwise filtered. * Update spacy/pipeline/span_ruler.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Fix cast * Add self.key property * Use number of patterns as length * Remove patterns kwarg from init * Update spacy/tests/pipeline/test_span_ruler.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Add options for spans filter and setting to ents * Add `spans_filter` option as a registered function' * Make `spans_key` optional and if `None`, set to `doc.ents` instead of `doc.spans[spans_key]`. * Update and generalize tests * Add test for setting doc.ents, fix key property type * Fix typing * Allow independent doc.spans and doc.ents * If `spans_key` is set, set `doc.spans` with `spans_filter`. * If `annotate_ents` is set, set `doc.ents` with `ents_fitler`. * Use `util.filter_spans` by default as `ents_filter`. * Use a custom warning if the filter does not work for `doc.ents`. * Enable use of SpanC.id in Span * Support id in SpanRuler as Span.id * Update types * `id` can only be provided as string (already by `PatternType` definition) * Update all uses of Span.id/ent_id in Doc * Rename Span id kwarg to span_id * Update types and docs * Add ents filter to mimic EntityRuler overwrite_ents * Refactor `ents_filter` to take `entities, spans` args for more filtering options * Give registered filters more descriptive names * Allow registered `filter_spans` filter (`spacy.first_longest_spans_filter.v1`) to take any number of `Iterable[Span]` objects as args so it can be used for spans filter or ents filter * Implement future entity ruler as span ruler Implement a compatible `entity_ruler` as `future_entity_ruler` using `SpanRuler` as the underlying component: * Add `sort_key` and `sort_reverse` to allow the sorting behavior to be customized. (Necessary for the same sorting/filtering as in `EntityRuler`.) * Implement `overwrite_overlapping_ents_filter` and `preserve_existing_ents_filter` to support `EntityRuler.overwrite_ents` settings. * Add `remove_by_id` to support `EntityRuler.remove` functionality. * Refactor `entity_ruler` tests to parametrize all tests to test both `entity_ruler` and `future_entity_ruler` * Implement `SpanRuler.token_patterns` and `SpanRuler.phrase_patterns` properties. Additional changes: * Move all config settings to top-level attributes to avoid duplicating settings in the config vs. `span_ruler/cfg`. (Also avoids a lot of casting.) * Format * Fix filter make method name * Refactor to use same error for removing by label or ID * Also provide existing spans to spans filter * Support ids property * Remove token_patterns and phrase_patterns * Update docstrings * Add span ruler docs * Fix types * Apply suggestions from code review Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Move sorting into filters * Check for all tokens in seen tokens in entity ruler filters * Remove registered sort key * Set Token.ent_id in a backwards-compatible way in Doc.set_ents * Remove sort options from API docs * Update docstrings * Rename entity ruler filters * Fix and parameterize scoring * Add id to Span API docs * Fix typo in API docs * Include explicit labeled=True for scorer Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
2022-06-02 14:12:53 +03:00
@id_.setter
def id_(self, str id_):
self.id = self.doc.vocab.strings.add(id_)
Add SpanRuler component (#9880) * Add SpanRuler component Add a `SpanRuler` component similar to `EntityRuler` that saves a list of matched spans to `Doc.spans[spans_key]`. The matches from the token and phrase matchers are deduplicated and sorted before assignment but are not otherwise filtered. * Update spacy/pipeline/span_ruler.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Fix cast * Add self.key property * Use number of patterns as length * Remove patterns kwarg from init * Update spacy/tests/pipeline/test_span_ruler.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Add options for spans filter and setting to ents * Add `spans_filter` option as a registered function' * Make `spans_key` optional and if `None`, set to `doc.ents` instead of `doc.spans[spans_key]`. * Update and generalize tests * Add test for setting doc.ents, fix key property type * Fix typing * Allow independent doc.spans and doc.ents * If `spans_key` is set, set `doc.spans` with `spans_filter`. * If `annotate_ents` is set, set `doc.ents` with `ents_fitler`. * Use `util.filter_spans` by default as `ents_filter`. * Use a custom warning if the filter does not work for `doc.ents`. * Enable use of SpanC.id in Span * Support id in SpanRuler as Span.id * Update types * `id` can only be provided as string (already by `PatternType` definition) * Update all uses of Span.id/ent_id in Doc * Rename Span id kwarg to span_id * Update types and docs * Add ents filter to mimic EntityRuler overwrite_ents * Refactor `ents_filter` to take `entities, spans` args for more filtering options * Give registered filters more descriptive names * Allow registered `filter_spans` filter (`spacy.first_longest_spans_filter.v1`) to take any number of `Iterable[Span]` objects as args so it can be used for spans filter or ents filter * Implement future entity ruler as span ruler Implement a compatible `entity_ruler` as `future_entity_ruler` using `SpanRuler` as the underlying component: * Add `sort_key` and `sort_reverse` to allow the sorting behavior to be customized. (Necessary for the same sorting/filtering as in `EntityRuler`.) * Implement `overwrite_overlapping_ents_filter` and `preserve_existing_ents_filter` to support `EntityRuler.overwrite_ents` settings. * Add `remove_by_id` to support `EntityRuler.remove` functionality. * Refactor `entity_ruler` tests to parametrize all tests to test both `entity_ruler` and `future_entity_ruler` * Implement `SpanRuler.token_patterns` and `SpanRuler.phrase_patterns` properties. Additional changes: * Move all config settings to top-level attributes to avoid duplicating settings in the config vs. `span_ruler/cfg`. (Also avoids a lot of casting.) * Format * Fix filter make method name * Refactor to use same error for removing by label or ID * Also provide existing spans to spans filter * Support ids property * Remove token_patterns and phrase_patterns * Update docstrings * Add span ruler docs * Fix types * Apply suggestions from code review Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Move sorting into filters * Check for all tokens in seen tokens in entity ruler filters * Remove registered sort key * Set Token.ent_id in a backwards-compatible way in Doc.set_ents * Remove sort options from API docs * Update docstrings * Rename entity ruler filters * Fix and parameterize scoring * Add id to Span API docs * Fix typo in API docs * Include explicit labeled=True for scorer Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
2022-06-02 14:12:53 +03:00
cdef int _count_words_to_root(const TokenC* token, int sent_length) except -1:
# Don't allow spaces to be the root, if there are
# better candidates
if Lexeme.c_check_flag(token.lex, IS_SPACE) and token.l_kids == 0 and token.r_kids == 0:
return sent_length-1
if Lexeme.c_check_flag(token.lex, IS_PUNCT) and token.l_kids == 0 and token.r_kids == 0:
return sent_length-1
cdef int n = 0
while token.head != 0:
token += token.head
n += 1
if n >= sent_length:
raise RuntimeError(Errors.E039)
return n