39 lines
1.4 KiB
Python
39 lines
1.4 KiB
Python
|
# Natural Language Toolkit: Transformation-based learning
|
||
|
|
#
|
||
|
|
# Copyright (C) 2001-2023 NLTK Project
|
||
|
|
# Author: Marcus Uneson <marcus.uneson@gmail.com>
|
||
|
|
# based on previous (nltk2) version by
|
||
|
|
# Christopher Maloof, Edward Loper, Steven Bird
|
||
|
|
# URL: <https://www.nltk.org/>
|
||
|
|
# For license information, see LICENSE.TXT
|
||
|
|
|
||
|
|
# 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 = f"{word}/{test_pos}->{train_pos}"
|
||
|
|
errors.append(f"{left[-25:]:>25} | {mid.center(22)} | {right[:25]}")
|
||
|
|
|
||
|
|
return errors
|