来自 OP 链接的paper，以下字符串：
叛乱分子在持续战斗中丧生
产量：
2-skip-bi-grams = {叛乱分子被杀，叛乱分子进入，叛乱分子
正在进行的, 被杀的, 被杀的 正在进行的, 被杀的战斗, 正在进行的, 在
战斗，持续战斗}
2-skip-tri-grams = {叛乱分子被杀，叛乱分子被杀正在进行，
叛乱分子打死战斗，叛乱分子在进行中，叛乱分子在
战斗, 叛乱分子 持续战斗, 被杀 持续, 被杀
战斗，杀死正在进行的战斗，正在进行的战斗}。
对 NLTK 的 ngrams 代码 (https://github.com/nltk/nltk/blob/develop/nltk/util.py#L383) 稍作修改：
from itertools import chain, combinations
import copy
from nltk.util import ngrams
def pad_sequence(sequence, n, pad_left=False, pad_right=False, pad_symbol=None):
if pad_left:
sequence = chain((pad_symbol,) * (n-1), sequence)
if pad_right:
sequence = chain(sequence, (pad_symbol,) * (n-1))
return sequence
def skipgrams(sequence, n, k, pad_left=False, pad_right=False, pad_symbol=None):
sequence_length = len(sequence)
sequence = iter(sequence)
sequence = pad_sequence(sequence, n, pad_left, pad_right, pad_symbol)
if sequence_length + pad_left + pad_right < k:
raise Exception("The length of sentence + padding(s) < skip")
if n < k:
raise Exception("Degree of Ngrams (n) needs to be bigger than skip (k)")
history = []
nk = n+k
# Return point for recursion.
if nk < 1:
return
# If n+k longer than sequence, reduce k by 1 and recur
elif nk > sequence_length:
for ng in skipgrams(list(sequence), n, k-1):
yield ng
while nk > 1: # Collects the first instance of n+k length history
history.append(next(sequence))
nk -= 1
# Iterative drop first item in history and picks up the next
# while yielding skipgrams for each iteration.
for item in sequence:
history.append(item)
current_token = history.pop(0)
# Iterates through the rest of the history and
# pick out all combinations the n-1grams
for idx in list(combinations(range(len(history)), n-1)):
ng = [current_token]
for _id in idx:
ng.append(history[_id])
yield tuple(ng)
# Recursively yield the skigrams for the rest of seqeunce where
# len(sequence) < n+k
for ng in list(skipgrams(history, n, k-1)):
yield ng
让我们做一些 doctest 来匹配论文中的例子：
>>> two_skip_bigrams = list(skipgrams(text, n=2, k=2))
[('Insurgents', 'killed'), ('Insurgents', 'in'), ('Insurgents', 'ongoing'), ('killed', 'in'), ('killed', 'ongoing'), ('killed', 'fighting'), ('in', 'ongoing'), ('in', 'fighting'), ('ongoing', 'fighting')]
>>> two_skip_trigrams = list(skipgrams(text, n=3, k=2))
[('Insurgents', 'killed', 'in'), ('Insurgents', 'killed', 'ongoing'), ('Insurgents', 'killed', 'fighting'), ('Insurgents', 'in', 'ongoing'), ('Insurgents', 'in', 'fighting'), ('Insurgents', 'ongoing', 'fighting'), ('killed', 'in', 'ongoing'), ('killed', 'in', 'fighting'), ('killed', 'ongoing', 'fighting'), ('in', 'ongoing', 'fighting')]
但请注意，如果n+k > len(sequence)，它将产生与skipgrams(sequence, n, k-1) 相同的效果（这不是错误，这是一个故障安全功能），例如
>>> three_skip_trigrams = list(skipgrams(text, n=3, k=3))
>>> three_skip_fourgrams = list(skipgrams(text, n=4, k=3))
>>> four_skip_fourgrams = list(skipgrams(text, n=4, k=4))
>>> four_skip_fivegrams = list(skipgrams(text, n=5, k=4))
>>>
>>> print len(three_skip_trigrams), three_skip_trigrams
10 [('Insurgents', 'killed', 'in'), ('Insurgents', 'killed', 'ongoing'), ('Insurgents', 'killed', 'fighting'), ('Insurgents', 'in', 'ongoing'), ('Insurgents', 'in', 'fighting'), ('Insurgents', 'ongoing', 'fighting'), ('killed', 'in', 'ongoing'), ('killed', 'in', 'fighting'), ('killed', 'ongoing', 'fighting'), ('in', 'ongoing', 'fighting')]
>>> print len(three_skip_fourgrams), three_skip_fourgrams
5 [('Insurgents', 'killed', 'in', 'ongoing'), ('Insurgents', 'killed', 'in', 'fighting'), ('Insurgents', 'killed', 'ongoing', 'fighting'), ('Insurgents', 'in', 'ongoing', 'fighting'), ('killed', 'in', 'ongoing', 'fighting')]
>>> print len(four_skip_fourgrams), four_skip_fourgrams
5 [('Insurgents', 'killed', 'in', 'ongoing'), ('Insurgents', 'killed', 'in', 'fighting'), ('Insurgents', 'killed', 'ongoing', 'fighting'), ('Insurgents', 'in', 'ongoing', 'fighting'), ('killed', 'in', 'ongoing', 'fighting')]
>>> print len(four_skip_fivegrams), four_skip_fivegrams
1 [('Insurgents', 'killed', 'in', 'ongoing', 'fighting')]
这允许n == k，但不允许n > k，如以下行所示：
if n < k:
raise Exception("Degree of Ngrams (n) needs to be bigger than skip (k)")
为了理解起见，让我们试着理解“神秘”的那一行：
for idx in list(combinations(range(len(history)), n-1)):
pass # Do something
给定一个独特项目的列表，组合产生这个：
>>> from itertools import combinations
>>> x = [0,1,2,3,4,5]
>>> list(combinations(x,2))
[(0, 1), (0, 2), (0, 3), (0, 4), (0, 5), (1, 2), (1, 3), (1, 4), (1, 5), (2, 3), (2, 4), (2, 5), (3, 4), (3, 5), (4, 5)]
而且由于标记列表的索引始终是唯一的，例如
>>> sent = ['this', 'is', 'a', 'foo', 'bar']
>>> current_token = sent.pop(0) # i.e. 'this'
>>> range(len(sent))
[0,1,2,3]
可以计算出可能的combinations (without replacement) 范围：
>>> n = 3
>>> list(combinations(range(len(sent)), n-1))
[(0, 1), (0, 2), (0, 3), (1, 2), (1, 3), (2, 3)]
如果我们将索引映射回标记列表：
>>> [tuple(sent[id] for id in idx) for idx in combinations(range(len(sent)), 2)
[('is', 'a'), ('is', 'foo'), ('is', 'bar'), ('a', 'foo'), ('a', 'bar'), ('foo', 'bar')]
然后我们与current_token 连接，我们得到当前标记和上下文+跳过窗口的skipgrams：
>>> [tuple([current_token]) + tuple(sent[id] for id in idx) for idx in combinations(range(len(sent)), 2)]
[('this', 'is', 'a'), ('this', 'is', 'foo'), ('this', 'is', 'bar'), ('this', 'a', 'foo'), ('this', 'a', 'bar'), ('this', 'foo', 'bar')]
然后我们继续下一个词。