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