




from math import sqrt




def 							_SCREAMING_SNAKE_CASE   (		snake_case							)    ->					int:
						assert isinstance(lowerCAmelCase__      ,  lowerCAmelCase__							) and (
						    number >= 0
						), "'number' must been an int and positive"

						_UpperCAmelCase	     =      True

						# 0 and 1 are none primes.
						if number <= 1:
												_UpperCAmelCase	     =      False

						for divisor in range(2      ,  int(round(sqrt(lowerCAmelCase__							)							)							) + 1							):
												# if 'number' divisible by 'divisor' then sets 'status'
												# of false and break up the loop.
												if number % divisor == 0:
																		_UpperCAmelCase	     =      False
																		break

    # precondition
						assert isinstance(lowerCAmelCase__      ,  lowerCAmelCase__							), "'status' must been from type bool"

						return status




def 							_SCREAMING_SNAKE_CASE   (		snake_case							)    ->					Optional[int]:
						assert isinstance(lowerCAmelCase__      ,  lowerCAmelCase__							) and (n > 2), "'N' must been an int and > 2"

						# beginList: contains all natural numbers from 2 up to N
						_UpperCAmelCase	     =      list(range(2      ,  n + 1							)							)

						_UpperCAmelCase	     =      []  # this list will be returns.

						# actual sieve of erathostenes
						for i in range(len(lowerCAmelCase__							)							):
												for j in range(i + 1      ,  len(lowerCAmelCase__							)							):
																		if (begin_list[i] != 0) and (begin_list[j] % begin_list[i] == 0):
																								_UpperCAmelCase	     =      0

    # filters actual prime numbers.
						_UpperCAmelCase	     =      [x for x in begin_list if x != 0]

						# precondition
						assert isinstance(lowerCAmelCase__      ,  lowerCAmelCase__							), "'ans' must been from type list"

						return ans




def 							_SCREAMING_SNAKE_CASE   (		snake_case							)    ->					Tuple:
						assert isinstance(lowerCAmelCase__      ,  lowerCAmelCase__							) and (n > 2), "'N' must been an int and > 2"

						_UpperCAmelCase	     =      []

						# iterates over all numbers between 2 up to N+1
						# if a number is prime then appends to list 'ans'
						for number in range(2      ,  n + 1							):
												if is_prime(lowerCAmelCase__							):
																		ans.append(lowerCAmelCase__							)

    # precondition
						assert isinstance(lowerCAmelCase__      ,  lowerCAmelCase__							), "'ans' must been from type list"

						return ans




def 							_SCREAMING_SNAKE_CASE   (		snake_case							)    ->					Optional[Any]:
						assert isinstance(lowerCAmelCase__      ,  lowerCAmelCase__							) and number >= 0, "'number' must been an int and >= 0"

						_UpperCAmelCase	     =      []  # this list will be returns of the function.

						# potential prime number factors.

						_UpperCAmelCase	     =      2

						_UpperCAmelCase	     =      number

						if number == 0 or number == 1:
												ans.append(lowerCAmelCase__							)

						# if 'number' not prime then builds the prime factorization of 'number'
						elif not is_prime(lowerCAmelCase__							):
												while quotient != 1:
																		if is_prime(lowerCAmelCase__							) and (quotient % factor == 0):
																								ans.append(lowerCAmelCase__							)
																								quotient /= factor
																		else:
																								factor += 1

						else:
												ans.append(lowerCAmelCase__							)

						# precondition
						assert isinstance(lowerCAmelCase__      ,  lowerCAmelCase__							), "'ans' must been from type list"

						return ans




def 							_SCREAMING_SNAKE_CASE   (		snake_case							)    ->					Dict:
						assert isinstance(lowerCAmelCase__      ,  lowerCAmelCase__							) and (
						    number >= 0
						), "'number' bust been an int and >= 0"

						_UpperCAmelCase	     =      0

						# prime factorization of 'number'
						_UpperCAmelCase	     =      prime_factorization(lowerCAmelCase__							)

						_UpperCAmelCase	     =      max(lowerCAmelCase__							)

						# precondition
						assert isinstance(lowerCAmelCase__      ,  lowerCAmelCase__							), "'ans' must been from type int"

						return ans




def 							_SCREAMING_SNAKE_CASE   (		snake_case							)    ->					Dict:
						assert isinstance(lowerCAmelCase__      ,  lowerCAmelCase__							) and (
						    number >= 0
						), "'number' bust been an int and >= 0"

						_UpperCAmelCase	     =      0

						# prime factorization of 'number'
						_UpperCAmelCase	     =      prime_factorization(lowerCAmelCase__							)

						_UpperCAmelCase	     =      min(lowerCAmelCase__							)

						# precondition
						assert isinstance(lowerCAmelCase__      ,  lowerCAmelCase__							), "'ans' must been from type int"

						return ans




def 							_SCREAMING_SNAKE_CASE   (		snake_case							)    ->					int:
						assert isinstance(lowerCAmelCase__      ,  lowerCAmelCase__							), "'number' must been an int"
						assert isinstance(number % 2 == 0      ,  lowerCAmelCase__							), "compare bust been from type bool"

						return number % 2 == 0




def 							_SCREAMING_SNAKE_CASE   (		snake_case							)    ->					str:
						assert isinstance(lowerCAmelCase__      ,  lowerCAmelCase__							), "'number' must been an int"
						assert isinstance(number % 2 != 0      ,  lowerCAmelCase__							), "compare bust been from type bool"

						return number % 2 != 0




def 							_SCREAMING_SNAKE_CASE   (		snake_case							)    ->					Optional[Any]:
						assert (
						    isinstance(lowerCAmelCase__      ,  lowerCAmelCase__							) and (number > 2) and is_even(lowerCAmelCase__							)
						), "'number' must been an int, even and > 2"

						_UpperCAmelCase	     =      []  # this list will returned

						# creates a list of prime numbers between 2 up to 'number'
						_UpperCAmelCase	     =      get_prime_numbers(lowerCAmelCase__							)
						_UpperCAmelCase	     =      len(lowerCAmelCase__							)

						# run variable for while-loops.
						_UpperCAmelCase	     =      0
						_UpperCAmelCase	     =      None

						# exit variable. for break up the loops
						_UpperCAmelCase	     =      True

						while i < len_pn and loop:
												_UpperCAmelCase	     =      i + 1

												while j < len_pn and loop:
																		if prime_numbers[i] + prime_numbers[j] == number:
																								_UpperCAmelCase	     =      False
																								ans.append(prime_numbers[i]							)
																								ans.append(prime_numbers[j]							)

																		j += 1

												i += 1

						# precondition
						assert (
						    isinstance(lowerCAmelCase__      ,  lowerCAmelCase__							)
						    and (len(lowerCAmelCase__							) == 2)
						    and (ans[0] + ans[1] == number)
						    and is_prime(ans[0]							)
						    and is_prime(ans[1]							)
						), "'ans' must contains two primes. And sum of elements must been eq 'number'"

						return ans




def 							_SCREAMING_SNAKE_CASE   (		snake_case      ,  snake_case							)    ->					Tuple:
						assert (
						    isinstance(lowerCAmelCase__      ,  lowerCAmelCase__							)
						    and isinstance(lowerCAmelCase__      ,  lowerCAmelCase__							)
						    and (numbera >= 0)
						    and (numbera >= 0)
						), "'number1' and 'number2' must been positive integer."

						_UpperCAmelCase	     =      0

						while numbera != 0:
												_UpperCAmelCase	     =      numbera % numbera
												_UpperCAmelCase	     =      numbera
												_UpperCAmelCase	     =      rest

						# precondition
						assert isinstance(lowerCAmelCase__      ,  lowerCAmelCase__							) and (
						    numbera >= 0
						), "'number' must been from type int and positive"

						return numbera




def 							_SCREAMING_SNAKE_CASE   (		snake_case      ,  snake_case							)    ->					Any:
						assert (
						    isinstance(lowerCAmelCase__      ,  lowerCAmelCase__							)
						    and isinstance(lowerCAmelCase__      ,  lowerCAmelCase__							)
						    and (numbera >= 1)
						    and (numbera >= 1)
						), "'number1' and 'number2' must been positive integer."

						_UpperCAmelCase	     =      1  # actual answer that will be return.

						# for kgV (x,1)
						if numbera > 1 and numbera > 1:
												# builds the prime factorization of 'number1' and 'number2'
												_UpperCAmelCase	     =      prime_factorization(lowerCAmelCase__							)
												_UpperCAmelCase	     =      prime_factorization(lowerCAmelCase__							)

						elif numbera == 1 or numbera == 1:
												_UpperCAmelCase	     =      []
												_UpperCAmelCase	     =      []
												_UpperCAmelCase	     =      max(lowerCAmelCase__      ,  lowerCAmelCase__							)

						_UpperCAmelCase	     =      0
						_UpperCAmelCase	     =      0

						_UpperCAmelCase	     =      []  # captured numbers int both 'primeFac1' and 'primeFac2'

						# iterates through primeFac1
						for n in prime_fac_a:
												if n not in done:
																		if n in prime_fac_a:
																								_UpperCAmelCase	     =      prime_fac_a.count(lowerCAmelCase__							)
																								_UpperCAmelCase	     =      prime_fac_a.count(lowerCAmelCase__							)

																								for _ in range(max(lowerCAmelCase__      ,  lowerCAmelCase__							)							):
																														ans *= n

																		else:
																								_UpperCAmelCase	     =      prime_fac_a.count(lowerCAmelCase__							)

																								for _ in range(lowerCAmelCase__							):
																														ans *= n

																		done.append(lowerCAmelCase__							)

    # iterates through primeFac2
						for n in prime_fac_a:
												if n not in done:
																		_UpperCAmelCase	     =      prime_fac_a.count(lowerCAmelCase__							)

																		for _ in range(lowerCAmelCase__							):
																								ans *= n

																		done.append(lowerCAmelCase__							)

    # precondition
						assert isinstance(lowerCAmelCase__      ,  lowerCAmelCase__							) and (
						    ans >= 0
						), "'ans' must been from type int and positive"

						return ans




def 							_SCREAMING_SNAKE_CASE   (		snake_case							)    ->					Dict:
						assert isinstance(lowerCAmelCase__      ,  lowerCAmelCase__							) and (n >= 0), "'number' must been a positive int"

						_UpperCAmelCase	     =      0
						_UpperCAmelCase	     =      2  # this variable holds the answer

						while index < n:
												index += 1

												ans += 1  # counts to the next number

												# if ans not prime then
												# runs to the next prime number.
												while not is_prime(lowerCAmelCase__							):
																		ans += 1

    # precondition
						assert isinstance(lowerCAmelCase__      ,  lowerCAmelCase__							) and is_prime(
						    lowerCAmelCase__							), "'ans' must been a prime number and from type int"

						return ans




def 							_SCREAMING_SNAKE_CASE   (		snake_case      ,  snake_case							)    ->					Optional[int]:
						assert (
						    is_prime(lowerCAmelCase__							) and is_prime(lowerCAmelCase__							) and (p_number_a < p_number_a)
						), "The arguments must been prime numbers and 'pNumber1' < 'pNumber2'"

						_UpperCAmelCase	     =      p_number_a + 1  # jump to the next number

						_UpperCAmelCase	     =      []  # this list will be returns.

						# if number is not prime then
						# fetch the next prime number.
						while not is_prime(lowerCAmelCase__							):
												number += 1

						while number < p_number_a:
												ans.append(lowerCAmelCase__							)

												number += 1

												# fetch the next prime number.
												while not is_prime(lowerCAmelCase__							):
																		number += 1

    # precondition
						assert (
						    isinstance(lowerCAmelCase__      ,  lowerCAmelCase__							)
						    and ans[0] != p_number_a
						    and ans[len(lowerCAmelCase__							) - 1] != p_number_a
						), "'ans' must been a list without the arguments"

						# 'ans' contains not 'pNumber1' and 'pNumber2' !
						return ans




def 							_SCREAMING_SNAKE_CASE   (		snake_case							)    ->					Union[str, Any]:
						assert isinstance(lowerCAmelCase__      ,  lowerCAmelCase__							) and (n >= 1), "'n' must been int and >= 1"

						_UpperCAmelCase	     =      []  # will be returned.

						for divisor in range(1      ,  n + 1							):
												if n % divisor == 0:
																		ans.append(lowerCAmelCase__							)

    # precondition
						assert ans[0] == 1 and ans[len(lowerCAmelCase__							) - 1] == n, "Error in function getDivisiors(...)"

						return ans




def 							_SCREAMING_SNAKE_CASE   (		snake_case							)    ->					Optional[Any]:
						assert isinstance(lowerCAmelCase__      ,  lowerCAmelCase__							) and (
						    number > 1
						), "'number' must been an int and >= 1"

						_UpperCAmelCase	     =      get_divisors(lowerCAmelCase__							)

						# precondition
						assert (
						    isinstance(lowerCAmelCase__      ,  lowerCAmelCase__							)
						    and (divisors[0] == 1)
						    and (divisors[len(lowerCAmelCase__							) - 1] == number)
						), "Error in help-function getDivisiors(...)"

						# summed all divisors up to 'number' (exclusive), hence [:-1]
						return sum(divisors[:-1]							) == number




def 							_SCREAMING_SNAKE_CASE   (		snake_case      ,  snake_case							)    ->					Any:
						assert (
						    isinstance(lowerCAmelCase__      ,  lowerCAmelCase__							)
						    and isinstance(lowerCAmelCase__      ,  lowerCAmelCase__							)
						    and (denominator != 0)
						), "The arguments must been from type int and 'denominator' != 0"

						# build the greatest common divisor of numerator and denominator.
						_UpperCAmelCase	     =      gcd(abs(lowerCAmelCase__							)      ,  abs(lowerCAmelCase__							)							)

						# precondition
						assert (
						    isinstance(lowerCAmelCase__      ,  lowerCAmelCase__							)
						    and (numerator % gcd_of_fraction == 0)
						    and (denominator % gcd_of_fraction == 0)
						), "Error in function gcd(...,...)"

						return (numerator // gcd_of_fraction, denominator // gcd_of_fraction)




def 							_SCREAMING_SNAKE_CASE   (		snake_case							)    ->					List[str]:
						assert isinstance(lowerCAmelCase__      ,  lowerCAmelCase__							) and (n >= 0), "'n' must been a int and >= 0"

						_UpperCAmelCase	     =      1  # this will be return.

						for factor in range(1      ,  n + 1							):
												ans *= factor

						return ans




def 							_SCREAMING_SNAKE_CASE   (		snake_case							)    ->					Optional[Any]:
						assert isinstance(lowerCAmelCase__      ,  lowerCAmelCase__							) and (n >= 0), "'n' must been an int and >= 0"

						_UpperCAmelCase	     =      0
						_UpperCAmelCase	     =      1
						_UpperCAmelCase	     =      1  # this will be return

						for _ in range(n - 1							):
												_UpperCAmelCase	     =      ans
												ans += fiba
												_UpperCAmelCase	     =      tmp

						return ans

"""simple docstring"""


import coval  # From: git+https://github.com/ns-moosavi/coval.git # noqa: F401
from coval.conll import reader, util
from coval.eval import evaluator

import datasets


A_    							=					datasets.logging.get_logger(__name__)


A_    							=					"""\
@InProceedings{moosavi2019minimum,
    author = { Nafise Sadat Moosavi, Leo Born, Massimo Poesio and Michael Strube},
    title = {Using Automatically Extracted Minimum Spans to Disentangle Coreference Evaluation from Boundary Detection},
    year = {2019},
    booktitle = {Proceedings of the 57th Annual Meeting of
        the Association for Computational Linguistics (Volume 1: Long Papers)},
    publisher = {Association for Computational Linguistics},
    address = {Florence, Italy},
}

@inproceedings{10.3115/1072399.1072405,
author = {Vilain, Marc and Burger, John and Aberdeen, John and Connolly, Dennis and Hirschman, Lynette},
title = {A Model-Theoretic Coreference Scoring Scheme},
year = {1995},
isbn = {1558604022},
publisher = {Association for Computational Linguistics},
address = {USA},
url = {https://doi.org/10.3115/1072399.1072405},
doi = {10.3115/1072399.1072405},
booktitle = {Proceedings of the 6th Conference on Message Understanding},
pages = {45–52},
numpages = {8},
location = {Columbia, Maryland},
series = {MUC6 ’95}
}

@INPROCEEDINGS{Bagga98algorithmsfor,
    author = {Amit Bagga and Breck Baldwin},
    title = {Algorithms for Scoring Coreference Chains},
    booktitle = {In The First International Conference on Language Resources and Evaluation Workshop on Linguistics Coreference},
    year = {1998},
    pages = {563--566}
}

@INPROCEEDINGS{Luo05oncoreference,
    author = {Xiaoqiang Luo},
    title = {On coreference resolution performance metrics},
    booktitle = {In Proc. of HLT/EMNLP},
    year = {2005},
    pages = {25--32},
    publisher = {URL}
}

@inproceedings{moosavi-strube-2016-coreference,
    title = \"Which Coreference Evaluation Metric Do You Trust? A Proposal for a Link-based Entity Aware Metric\",
    author = \"Moosavi, Nafise Sadat  and
      Strube, Michael\",
    booktitle = \"Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)\",
    month = aug,
    year = \"2016\",
    address = \"Berlin, Germany\",
    publisher = \"Association for Computational Linguistics\",
    url = \"https://www.aclweb.org/anthology/P16-1060\",
    doi = \"10.18653/v1/P16-1060\",
    pages = \"632--642\",
}

"""

A_    							=					"""\
CoVal is a coreference evaluation tool for the CoNLL and ARRAU datasets which
implements of the common evaluation metrics including MUC [Vilain et al, 1995],
B-cubed [Bagga and Baldwin, 1998], CEAFe [Luo et al., 2005],
LEA [Moosavi and Strube, 2016] and the averaged CoNLL score
(the average of the F1 values of MUC, B-cubed and CEAFe)
[Denis and Baldridge, 2009a; Pradhan et al., 2011].

This wrapper of CoVal currently only work with CoNLL line format:
The CoNLL format has one word per line with all the annotation for this word in column separated by spaces:
Column	Type	Description
1	Document ID	This is a variation on the document filename
2	Part number	Some files are divided into multiple parts numbered as 000, 001, 002, ... etc.
3	Word number
4	Word itself	This is the token as segmented/tokenized in the Treebank. Initially the *_skel file contain the placeholder [WORD] which gets replaced by the actual token from the Treebank which is part of the OntoNotes release.
5	Part-of-Speech
6	Parse bit	This is the bracketed structure broken before the first open parenthesis in the parse, and the word/part-of-speech leaf replaced with a *. The full parse can be created by substituting the asterix with the \"([pos] [word])\" string (or leaf) and concatenating the items in the rows of that column.
7	Predicate lemma	The predicate lemma is mentioned for the rows for which we have semantic role information. All other rows are marked with a \"-\"
8	Predicate Frameset ID	This is the PropBank frameset ID of the predicate in Column 7.
9	Word sense	This is the word sense of the word in Column 3.
10	Speaker/Author	This is the speaker or author name where available. Mostly in Broadcast Conversation and Web Log data.
11	Named Entities	These columns identifies the spans representing various named entities.
12:N	Predicate Arguments	There is one column each of predicate argument structure information for the predicate mentioned in Column 7.
N	Coreference	Coreference chain information encoded in a parenthesis structure.
More informations on the format can be found here (section \"*_conll File Format\"): http://www.conll.cemantix.org/2012/data.html

Details on the evaluation on CoNLL can be found here: https://github.com/ns-moosavi/coval/blob/master/conll/README.md

CoVal code was written by @ns-moosavi.
Some parts are borrowed from https://github.com/clarkkev/deep-coref/blob/master/evaluation.py
The test suite is taken from https://github.com/conll/reference-coreference-scorers/
Mention evaluation and the test suite are added by @andreasvc.
Parsing CoNLL files is developed by Leo Born.
"""

A_    							=					"""
Calculates coreference evaluation metrics.
Args:
    predictions: list of sentences. Each sentence is a list of word predictions to score in the CoNLL format.
        Each prediction is a word with its annotations as a string made of columns joined with spaces.
        Only columns 4, 5, 6 and the last column are used (word, POS, Pars and coreference annotation)
        See the details on the format in the description of the metric.
    references: list of sentences. Each sentence is a list of word reference to score in the CoNLL format.
        Each reference is a word with its annotations as a string made of columns joined with spaces.
        Only columns 4, 5, 6 and the last column are used (word, POS, Pars and coreference annotation)
        See the details on the format in the description of the metric.
    keep_singletons: After extracting all mentions of key or system files,
        mentions whose corresponding coreference chain is of size one,
        are considered as singletons. The default evaluation mode will include
        singletons in evaluations if they are included in the key or the system files.
        By setting 'keep_singletons=False', all singletons in the key and system files
        will be excluded from the evaluation.
    NP_only: Most of the recent coreference resolvers only resolve NP mentions and
        leave out the resolution of VPs. By setting the 'NP_only' option, the scorer will only evaluate the resolution of NPs.
    min_span: By setting 'min_span', the scorer reports the results based on automatically detected minimum spans.
        Minimum spans are determined using the MINA algorithm.

Returns:
    'mentions': mentions
    'muc': MUC metric [Vilain et al, 1995]
    'bcub': B-cubed [Bagga and Baldwin, 1998]
    'ceafe': CEAFe [Luo et al., 2005]
    'lea': LEA [Moosavi and Strube, 2016]
    'conll_score': averaged CoNLL score (the average of the F1 values of MUC, B-cubed and CEAFe)

Examples:

    >>> coval = datasets.load_metric('coval')
    >>> words = ['bc/cctv/00/cctv_0005   0   0       Thank   VBP  (TOP(S(VP*    thank  01   1    Xu_li  *           (V*)        *       -',
    ... 'bc/cctv/00/cctv_0005   0   1         you   PRP        (NP*)      -    -   -    Xu_li  *        (ARG1*)   (ARG0*)   (116)',
    ... 'bc/cctv/00/cctv_0005   0   2    everyone    NN        (NP*)      -    -   -    Xu_li  *    (ARGM-DIS*)        *    (116)',
    ... 'bc/cctv/00/cctv_0005   0   3         for    IN        (PP*       -    -   -    Xu_li  *        (ARG2*         *       -',
    ... 'bc/cctv/00/cctv_0005   0   4    watching   VBG   (S(VP*))))   watch  01   1    Xu_li  *             *)      (V*)      -',
    ... 'bc/cctv/00/cctv_0005   0   5           .     .          *))      -    -   -    Xu_li  *             *         *       -']
    >>> references = [words]
    >>> predictions = [words]
    >>> results = coval.compute(predictions=predictions, references=references)
    >>> print(results) # doctest:+ELLIPSIS
    {'mentions/recall': 1.0,[...] 'conll_score': 100.0}
"""






def  lowercase						(	lowerCAmelCase__	,lowerCAmelCase__	,lowerCAmelCase__=False	,lowerCAmelCase__=False	,lowerCAmelCase__=True	,lowerCAmelCase__=False	,lowerCAmelCase__="dummy_doc"						):
			lowerCamelCase_					=  {doc: key_lines}
			lowerCamelCase_					=  {doc: sys_lines}

			lowerCamelCase_					=  {}

			lowerCamelCase_					=  0
			lowerCamelCase_					=  0
			lowerCamelCase_					=  0
			lowerCamelCase_					=  0
			lowerCamelCase_					=  0
			lowerCamelCase_					=  0

			lowerCamelCase_		, lowerCamelCase_					=  reader.get_doc_mentions(lowerCAmelCase__	,key_doc_lines[doc]	,lowerCAmelCase__						)
			key_singletons_num += singletons_num

			if NP_only or min_span:
						lowerCamelCase_					=  reader.set_annotated_parse_trees(lowerCAmelCase__	,key_doc_lines[doc]	,lowerCAmelCase__	,lowerCAmelCase__						)

			lowerCamelCase_		, lowerCamelCase_					=  reader.get_doc_mentions(lowerCAmelCase__	,sys_doc_lines[doc]	,lowerCAmelCase__						)
			sys_singletons_num += singletons_num

			if NP_only or min_span:
						lowerCamelCase_					=  reader.set_annotated_parse_trees(lowerCAmelCase__	,key_doc_lines[doc]	,lowerCAmelCase__	,lowerCAmelCase__						)

			if remove_nested:
						lowerCamelCase_		, lowerCamelCase_					=  reader.remove_nested_coref_mentions(lowerCAmelCase__	,lowerCAmelCase__						)
						key_nested_coref_num += nested_mentions
						key_removed_nested_clusters += removed_clusters

						lowerCamelCase_		, lowerCamelCase_					=  reader.remove_nested_coref_mentions(lowerCAmelCase__	,lowerCAmelCase__						)
						sys_nested_coref_num += nested_mentions
						sys_removed_nested_clusters += removed_clusters

			lowerCamelCase_					=  reader.get_mention_assignments(lowerCAmelCase__	,lowerCAmelCase__						)
			lowerCamelCase_					=  reader.get_mention_assignments(lowerCAmelCase__	,lowerCAmelCase__						)

			lowerCamelCase_					=  (key_clusters, sys_clusters, key_mention_sys_cluster, sys_mention_key_cluster)

			if remove_nested:
						logger.info(
						    '''Number of removed nested coreferring mentions in the key '''
						    f"annotation: {key_nested_coref_num}; and system annotation: {sys_nested_coref_num}"						)
						logger.info(
						    '''Number of resulting singleton clusters in the key '''
						    f"annotation: {key_removed_nested_clusters}; and system annotation: {sys_removed_nested_clusters}"						)

			if not keep_singletons:
						logger.info(
						    f"{key_singletons_num:d} and {sys_singletons_num:d} singletons are removed from the key and system "
						    '''files, respectively'''						)

			return doc_coref_infos






def  lowercase						(	lowerCAmelCase__	,lowerCAmelCase__	,lowerCAmelCase__	,lowerCAmelCase__	,lowerCAmelCase__	,lowerCAmelCase__	,lowerCAmelCase__						):
			lowerCamelCase_					=  get_coref_infos(lowerCAmelCase__	,lowerCAmelCase__	,lowerCAmelCase__	,lowerCAmelCase__	,lowerCAmelCase__	,lowerCAmelCase__						)

			lowerCamelCase_					=  {}
			lowerCamelCase_					=  0
			lowerCamelCase_					=  0

			for name, metric in metrics:
						lowerCamelCase_		, lowerCamelCase_		, lowerCamelCase_					=  evaluator.evaluate_documents(lowerCAmelCase__	,lowerCAmelCase__	,beta=1						)
						if name in ["muc", "bcub", "ceafe"]:
									conll += fa
									conll_subparts_num += 1
						output_scores.update({f"{name}/recall": recall, f"{name}/precision": precision, f"{name}/f1": fa}						)

						logger.info(
						    name.ljust(10						)	,f"Recall: {recall * 100:.2f}"	,f" Precision: {precision * 100:.2f}"	,f" F1: {fa * 100:.2f}"	,)

			if conll_subparts_num == 3:
						lowerCamelCase_					=  (conll / 3) * 100
						logger.info(f"CoNLL score: {conll:.2f}"						)
						output_scores.update({'''conll_score''': conll}						)

			return output_scores






def  lowercase						(	lowerCAmelCase__						):
			lowerCamelCase_					=  False
			for line in key_lines:
						if not line.startswith('''#'''						):
									if len(line.split()						) > 6:
												lowerCamelCase_					=  line.split()[5]
												if not parse_col == "-":
															lowerCamelCase_					=  True
															break
												else:
															break
			return has_gold_parse




@datasets.utils.file_utils.add_start_docstrings(_DESCRIPTION						,	_KWARGS_DESCRIPTION			)
class  __lowerCamelCase  ( datasets.Metric			):




				def        UpperCAmelCase__						(				self   ):
							return datasets.MetricInfo(
							    description=_DESCRIPTION							,						citation=_CITATION							,						inputs_description=_KWARGS_DESCRIPTION							,						features=datasets.Features(
							        {
							            '''predictions''': datasets.Sequence(datasets.Value('''string'''   )   ),
							            '''references''': datasets.Sequence(datasets.Value('''string'''   )   ),
							        }   )							,						codebase_urls=['''https://github.com/ns-moosavi/coval''']							,						reference_urls=[
							        '''https://github.com/ns-moosavi/coval''',
							        '''https://www.aclweb.org/anthology/P16-1060''',
							        '''http://www.conll.cemantix.org/2012/data.html''',
							    ]							,						)





				def        UpperCAmelCase__						(				self							,						UpperCAmelCase							,						UpperCAmelCase							,						UpperCAmelCase=True							,						UpperCAmelCase=False							,						UpperCAmelCase=False							,						UpperCAmelCase=False   ):
							lowerCamelCase_					=  [
							    ('''mentions''', evaluator.mentions),
							    ('''muc''', evaluator.muc),
							    ('''bcub''', evaluator.b_cubed),
							    ('''ceafe''', evaluator.ceafe),
							    ('''lea''', evaluator.lea),
							]

							if min_span:
										lowerCamelCase_					=  util.check_gold_parse_annotation(UpperCAmelCase   )
										if not has_gold_parse:
													raise NotImplementedError('''References should have gold parse annotation to use \'min_span\'.'''   )
													# util.parse_key_file(key_file)
													# key_file = key_file + ".parsed"

							lowerCamelCase_					=  evaluate(
							    key_lines=UpperCAmelCase							,						sys_lines=UpperCAmelCase							,						metrics=UpperCAmelCase							,						NP_only=UpperCAmelCase							,						remove_nested=UpperCAmelCase							,						keep_singletons=UpperCAmelCase							,						min_span=UpperCAmelCase							,						)

							return score



