Nltk: find_concordance () mengembalikan daftar kosong untuk left_context

Dibuat pada 20 Agu 2018 · 4Komentar · Sumber: nltk/nltk

if offsets:
            for i in offsets:
                query_word = self._tokens[i]
                # Find the context of query word.
                left_context = self._tokens[i-context:i]

Jika kemunculan pertama istilah penelusuran berada di awal teks (misalnya di offset 7), misalkan parameter lebar disetel ke 20, maka [i- context: i ] akan dievaluasi sebagai [-13: 7] .
Dalam kasus ini, jika teks terdiri lebih dari 20 kata, variabel left_context akan menjadi daftar kosong, bukan daftar yang berisi 7 kata pertama dari teks.

Perbaikan sederhana akan dilakukan:

if offsets:
    for i in offsets:
        query_word = self._tokens[i]
        # Find the context of query word.
        if i - context < 0:
            left_context = self._tokens[:i]
        else:
            left_context = self._tokens[i-context:i]

bug corpus goodfirstbug

Sumber

BLKSerene

Semua 4 komentar

Bisakah Anda memberikan masukan sampel dan keluaran yang diinginkan sehingga kami dapat menambahkan ke uji regresi?

alvations pada 20 Agu 2018

Memasukkan:

jane_eyre = 'Chapter 1\nTHERE was no possibility of taking a walk that day. We had been wandering, indeed, in the leafless shrubbery an hour in the morning; but since dinner (Mrs. Reed, when there was no company, dined early) the cold winter wind had brought with it clouds so sombre, and a rain so penetrating, that further outdoor exercise was now out of the question.'
text = nltk.Text(nltk.word_tokenize(jane_eyre))
text.concordance('taking')
text.concordance_list('taking')[0]

Keluaran (NLTK 3.3):

Displaying 1 of 1 matches:
    taking a walk that day . We had been wander
ConcordanceLine(left=[],
                query='taking',
                right=['a', 'walk', 'that', 'day', '.', 'We', 'had', 'been', 'wandering', ',', 'indeed', ',', 'in', 'the', 'leafless', 'shrubbery', 'an', 'hour'],
                offset=7,
                left_print='',
                right_print='a walk that day . We had been wande',
                line=' taking a walk that day . We had been wande')

Output yang Diinginkan:

Displaying 1 of 1 matches:
    Chapter 1 THERE was no possibility of taking a walk that day . We had been wander
ConcordanceLine(left=['Chapter', '1', 'THERE', 'was', 'no', 'possibility', 'of'],
                query='taking',
                right=['a', 'walk', 'that', 'day', '.', 'We', 'had', 'been', 'wandering', ',', 'indeed', ',', 'in', 'the', 'leafless', 'shrubbery', 'an', 'hour'],
                offset=7,
                left_print='Chapter 1 THERE was no possibility of',
                right_print='a walk that day . We had been wande',
                line='Chapter 1 THERE was no possibility of taking a walk that day . We had been wande')

BLKSerene pada 21 Agu 2018

👍1

Terima kasih @BLKSerene telah melaporkan bug!

Ah, ada perbaikan keren di sini. Alih-alih jika-lain. Kita dapat memotong batas minimum menjadi max() , misalnya

left_context = self._tokens[max(0, i-context):i]

Menambahkan doctest ke https://github.com/nltk/nltk/blob/develop/nltk/test/concordance.doctest untuk uji integrasi / regresi berkelanjutan akan sangat membantu =)

Patching https://github.com/nltk/nltk/issues/2088
The left slice of the left context should be clip to 0 if the `i-context` < 0.

>>> from nltk import Text, word_tokenize
>>> jane_eyre = 'Chapter 1\nTHERE was no possibility of taking a walk that day. We had been wandering, indeed, in the leafless shrubbery an hour in the morning; but since dinner (Mrs. Reed, when there was no company, dined early) the cold winter wind had brought with it clouds so sombre, and a rain so penetrating, that further outdoor exercise was now out of the question.'
>>> text = Text(word_tokenize(jane_eyre))
>>> text.concordance_list('taking')[0].left
['Chapter', '1', 'THERE', 'was', 'no', 'possibility', 'of']

alvations pada 23 Agu 2018

👍1

Ditambal di # 2103. Terima kasih @BLKSerene dan @ dnc1994!

alvations pada 19 Sep 2018

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