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e962784531
* Add Lemmatizer and simplify related components * Add `Lemmatizer` pipe with `lookup` and `rule` modes using the `Lookups` tables. * Reduce `Tagger` to a simple tagger that sets `Token.tag` (no pos or lemma) * Reduce `Morphology` to only keep track of morph tags (no tag map, lemmatizer, or morph rules) * Remove lemmatizer from `Vocab` * Adjust many many tests Differences: * No default lookup lemmas * No special treatment of TAG in `from_array` and similar required * Easier to modify labels in a `Tagger` * No extra strings added from morphology / tag map * Fix test * Initial fix for Lemmatizer config/serialization * Adjust init test to be more generic * Adjust init test to force empty Lookups * Add simple cache to rule-based lemmatizer * Convert language-specific lemmatizers Convert language-specific lemmatizers to component lemmatizers. Remove previous lemmatizer class. * Fix French and Polish lemmatizers * Remove outdated UPOS conversions * Update Russian lemmatizer init in tests * Add minimal init/run tests for custom lemmatizers * Add option to overwrite existing lemmas * Update mode setting, lookup loading, and caching * Make `mode` an immutable property * Only enforce strict `load_lookups` for known supported modes * Move caching into individual `_lemmatize` methods * Implement strict when lang is not found in lookups * Fix tables/lookups in make_lemmatizer * Reallow provided lookups and allow for stricter checks * Add lookups asset to all Lemmatizer pipe tests * Rename lookups in lemmatizer init test * Clean up merge * Refactor lookup table loading * Add helper from `load_lemmatizer_lookups` that loads required and optional lookups tables based on settings provided by a config. Additional slight refactor of lookups: * Add `Lookups.set_table` to set a table from a provided `Table` * Reorder class definitions to be able to specify type as `Table` * Move registry assets into test methods * Refactor lookups tables config Use class methods within `Lemmatizer` to provide the config for particular modes and to load the lookups from a config. * Add pipe and score to lemmatizer * Simplify Tagger.score * Add missing import * Clean up imports and auto-format * Remove unused kwarg * Tidy up and auto-format * Update docstrings for Lemmatizer Update docstrings for Lemmatizer. Additionally modify `is_base_form` API to take `Token` instead of individual features. * Update docstrings * Remove tag map values from Tagger.add_label * Update API docs * Fix relative link in Lemmatizer API docs
129 lines
4.6 KiB
Python
129 lines
4.6 KiB
Python
from typing import List, Dict
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from ...pipeline import Lemmatizer
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from ...tokens import Token
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class DutchLemmatizer(Lemmatizer):
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@classmethod
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def get_lookups_config(cls, mode: str) -> Dict:
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if mode == "rule":
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return {
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"required_tables": [
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"lemma_lookup",
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"lemma_rules",
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"lemma_exc",
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"lemma_index",
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],
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}
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else:
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return super().get_lookups_config(mode)
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def lookup_lemmatize(self, token: Token) -> List[str]:
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"""Overrides parent method so that a lowercased version of the string
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is used to search the lookup table. This is necessary because our
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lookup table consists entirely of lowercase keys."""
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lookup_table = self.lookups.get_table("lemma_lookup", {})
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string = token.text.lower()
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return [lookup_table.get(string, string)]
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# Note: CGN does not distinguish AUX verbs, so we treat AUX as VERB.
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def rule_lemmatize(self, token: Token) -> List[str]:
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# Difference 1: self.rules is assumed to be non-None, so no
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# 'is None' check required.
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# String lowercased from the get-go. All lemmatization results in
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# lowercased strings. For most applications, this shouldn't pose
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# any problems, and it keeps the exceptions indexes small. If this
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# creates problems for proper nouns, we can introduce a check for
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# univ_pos == "PROPN".
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cache_key = (token.lower, token.pos)
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if cache_key in self.cache:
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return self.cache[cache_key]
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string = token.text
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univ_pos = token.pos_.lower()
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if univ_pos in ("", "eol", "space"):
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forms = [string.lower()]
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self.cache[cache_key] = forms
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return forms
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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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index = index_table.get(univ_pos, {})
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exceptions = exc_table.get(univ_pos, {})
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rules = rules_table.get(univ_pos, {})
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string = string.lower()
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if univ_pos not in (
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"noun",
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"verb",
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"aux",
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"adj",
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"adv",
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"pron",
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"det",
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"adp",
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"num",
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):
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forms = [string]
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self.cache[cache_key] = forms
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return forms
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lemma_index = index_table.get(univ_pos, {})
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# string is already lemma
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if string in lemma_index:
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forms = [string]
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self.cache[cache_key] = forms
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return forms
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exc_table = self.lookups.get_table("lemma_exc", {})
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exceptions = exc_table.get(univ_pos, {})
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# string is irregular token contained in exceptions index.
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try:
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forms = [exceptions[string][0]]
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self.cache[cache_key] = forms
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return forms
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except KeyError:
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pass
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# string corresponds to key in lookup table
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lookup_table = self.lookups.get_table("lemma_lookup", {})
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looked_up_lemma = lookup_table.get(string)
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if looked_up_lemma and looked_up_lemma in lemma_index:
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forms = [looked_up_lemma]
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self.cache[cache_key] = forms
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return forms
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rules_table = self.lookups.get_table("lemma_rules", {})
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oov_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:
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forms = [form]
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self.cache[cache_key] = forms
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return forms
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else:
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oov_forms.append(form)
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forms = list(set(oov_forms))
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# Back-off through remaining return value candidates.
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if forms:
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for form in forms:
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if form in exceptions:
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forms = [form]
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self.cache[cache_key] = forms
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return forms
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if looked_up_lemma:
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forms = [looked_up_lemma]
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self.cache[cache_key] = forms
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return forms
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else:
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self.cache[cache_key] = forms
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return forms
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elif looked_up_lemma:
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forms = [looked_up_lemma]
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self.cache[cache_key] = forms
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return forms
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else:
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forms = [string]
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self.cache[cache_key] = forms
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return forms
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