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Python

5 years ago
# -*- coding: utf-8 -*-
# Natural Language Toolkit: Transformation-based learning
#
# Copyright (C) 2001-2019 NLTK Project
# Author: Marcus Uneson <marcus.uneson@gmail.com>
# based on previous (nltk2) version by
# Christopher Maloof, Edward Loper, Steven Bird
# URL: <http://nltk.org/>
# For license information, see LICENSE.TXT
from __future__ import print_function
# returns a list of errors in string format
def error_list(train_sents, test_sents):
"""
Returns a list of human-readable strings indicating the errors in the
given tagging of the corpus.
:param train_sents: The correct tagging of the corpus
:type train_sents: list(tuple)
:param test_sents: The tagged corpus
:type test_sents: list(tuple)
"""
hdr = ('%25s | %s | %s\n' + '-' * 26 + '+' + '-' * 24 + '+' + '-' * 26) % (
'left context',
'word/test->gold'.center(22),
'right context',
)
errors = [hdr]
for (train_sent, test_sent) in zip(train_sents, test_sents):
for wordnum, (word, train_pos) in enumerate(train_sent):
test_pos = test_sent[wordnum][1]
if train_pos != test_pos:
left = ' '.join('%s/%s' % w for w in train_sent[:wordnum])
right = ' '.join('%s/%s' % w for w in train_sent[wordnum + 1 :])
mid = '%s/%s->%s' % (word, test_pos, train_pos)
errors.append(
'%25s | %s | %s' % (left[-25:], mid.center(22), right[:25])
)
return errors