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https://github.com/explosion/spaCy.git
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* Update with WIP * Update with WIP * Update with pipeline serialization * Update types and pipe factories * Add deep merge, tidy up and add tests * Fix pipe creation from config * Don't validate default configs on load * Update spacy/language.py Co-authored-by: Ines Montani <ines@ines.io> * Adjust factory/component meta error * Clean up factory args and remove defaults * Add test for failing empty dict defaults * Update pipeline handling and methods * provide KB as registry function instead of as object * small change in test to make functionality more clear * update example script for EL configuration * Fix typo * Simplify test * Simplify test * splitting pipes.pyx into separate files * moving default configs to each component file * fix batch_size type * removing default values from component constructors where possible (TODO: test 4725) * skip instead of xfail * Add test for config -> nlp with multiple instances * pipeline.pipes -> pipeline.pipe * Tidy up, document, remove kwargs * small cleanup/generalization for Tok2VecListener * use DEFAULT_UPSTREAM field * revert to avoid circular imports * Fix tests * Replace deprecated arg * Make model dirs require config * fix pickling of keyword-only arguments in constructor * WIP: clean up and integrate full config * Add helper to handle function args more reliably Now also includes keyword-only args * Fix config composition and serialization * Improve config debugging and add visual diff * Remove unused defaults and fix type * Remove pipeline and factories from meta * Update spacy/default_config.cfg Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/default_config.cfg * small UX edits * avoid printing stack trace for debug CLI commands * Add support for language-specific factories * specify the section of the config which holds the model to debug * WIP: add Language.from_config * Update with language data refactor WIP * Auto-format * Add backwards-compat handling for Language.factories * Update morphologizer.pyx * Fix morphologizer * Update and simplify lemmatizers * Fix Japanese tests * Port over tagger changes * Fix Chinese and tests * Update to latest Thinc * WIP: xfail first Russian lemmatizer test * Fix component-specific overrides * fix nO for output layers in debug_model * Fix default value * Fix tests and don't pass objects in config * Fix deep merging * Fix lemma lookup data registry Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed) * Add types * Add Vocab.from_config * Fix typo * Fix tests * Make config copying more elegant * Fix pipe analysis * Fix lemmatizers and is_base_form * WIP: move language defaults to config * Fix morphology type * Fix vocab * Remove comment * Update to latest Thinc * Add morph rules to config * Tidy up * Remove set_morphology option from tagger factory * Hack use_gpu * Move [pipeline] to top-level block and make [nlp.pipeline] list Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them * Fix use_gpu and resume in CLI * Auto-format * Remove resume from config * Fix formatting and error * [pipeline] -> [components] * Fix types * Fix tagger test: requires set_morphology? Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
135 lines
4.7 KiB
Python
135 lines
4.7 KiB
Python
from typing import Optional, List, Dict
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from ...lemmatizer import Lemmatizer
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from ...symbols import POS, NOUN, VERB, ADJ, ADV, PRON, DET, AUX, PUNCT, ADP
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from ...symbols import SCONJ, CCONJ
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class FrenchLemmatizer(Lemmatizer):
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"""
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French language lemmatizer applies the default rule based lemmatization
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procedure with some modifications for better French language support.
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The parts of speech 'ADV', 'PRON', 'DET', 'ADP' and 'AUX' are added to use
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the rule-based lemmatization. As a last resort, the lemmatizer checks in
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the lookup table.
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"""
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def __call__(
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self, string: str, univ_pos: str, morphology: Optional[dict] = None
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) -> List[str]:
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lookup_table = self.lookups.get_table("lemma_lookup", {})
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if "lemma_rules" not in self.lookups:
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return [lookup_table.get(string, string)]
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if univ_pos in (NOUN, "NOUN", "noun"):
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univ_pos = "noun"
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elif univ_pos in (VERB, "VERB", "verb"):
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univ_pos = "verb"
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elif univ_pos in (ADJ, "ADJ", "adj"):
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univ_pos = "adj"
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elif univ_pos in (ADP, "ADP", "adp"):
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univ_pos = "adp"
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elif univ_pos in (ADV, "ADV", "adv"):
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univ_pos = "adv"
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elif univ_pos in (AUX, "AUX", "aux"):
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univ_pos = "aux"
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elif univ_pos in (CCONJ, "CCONJ", "cconj"):
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univ_pos = "cconj"
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elif univ_pos in (DET, "DET", "det"):
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univ_pos = "det"
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elif univ_pos in (PRON, "PRON", "pron"):
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univ_pos = "pron"
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elif univ_pos in (PUNCT, "PUNCT", "punct"):
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univ_pos = "punct"
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elif univ_pos in (SCONJ, "SCONJ", "sconj"):
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univ_pos = "sconj"
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else:
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return [self.lookup(string)]
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index_table = self.lookups.get_table("lemma_index", {})
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exc_table = self.lookups.get_table("lemma_exc", {})
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rules_table = self.lookups.get_table("lemma_rules", {})
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lemmas = self.lemmatize(
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string,
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index_table.get(univ_pos, {}),
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exc_table.get(univ_pos, {}),
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rules_table.get(univ_pos, []),
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)
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return lemmas
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def lookup(self, string: str, orth: Optional[int] = None) -> str:
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lookup_table = self.lookups.get_table("lemma_lookup", {})
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if orth is not None and orth in lookup_table:
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return lookup_table[orth][0]
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return string
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def lemmatize(
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self,
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string: str,
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index: Dict[str, List[str]],
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exceptions: Dict[str, Dict[str, List[str]]],
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rules: Dict[str, List[List[str]]],
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) -> List[str]:
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lookup_table = self.lookups.get_table("lemma_lookup", {})
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string = string.lower()
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forms = []
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if string in index:
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forms.append(string)
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return forms
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forms.extend(exceptions.get(string, []))
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oov_forms = []
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if not forms:
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for old, new in rules:
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if string.endswith(old):
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form = string[: len(string) - len(old)] + new
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if not form:
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pass
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elif form in index or not form.isalpha():
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forms.append(form)
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else:
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oov_forms.append(form)
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if not forms:
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forms.extend(oov_forms)
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if not forms and string in lookup_table.keys():
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forms.append(lookup_table[string][0])
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if not forms:
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forms.append(string)
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return list(set(forms))
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def is_base_form(univ_pos: str, morphology: Optional[dict] = None) -> bool:
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"""
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Check whether we're dealing with an uninflected paradigm, so we can
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avoid lemmatization entirely.
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"""
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morphology = {} if morphology is None else morphology
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others = [
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key
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for key in morphology
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if key not in (POS, "Number", "POS", "VerbForm", "Tense")
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]
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if univ_pos == "noun" and morphology.get("Number") == "sing":
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return True
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elif univ_pos == "verb" and morphology.get("VerbForm") == "inf":
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return True
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# This maps 'VBP' to base form -- probably just need 'IS_BASE'
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# morphology
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elif univ_pos == "verb" and (
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morphology.get("VerbForm") == "fin"
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and morphology.get("Tense") == "pres"
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and morphology.get("Number") is None
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and not others
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):
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return True
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elif univ_pos == "adj" and morphology.get("Degree") == "pos":
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return True
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elif "VerbForm=inf" in morphology:
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return True
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elif "VerbForm=none" in morphology:
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return True
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elif "Number=sing" in morphology:
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return True
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elif "Degree=pos" in morphology:
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return True
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else:
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return False
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