大家知道"a man of woman"的意思吗?

本文通过具体例子解析了英语中的一种特殊表达方式:使用'a[an]+名词(1)+of+a[an,that,物主代词]+名词(2)'结构来表示‘像(1)的(2)’或‘(1)般的(2)’的意思,并鼓励读者发挥想象思考更多类似用法。

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[例句]Angela is a man of a woman.
[误译]安吉拉是个有妇之夫。
[原意]安吉拉是个像男人的女人。
[说明]a[an] + 名词(1)+ of + a [an, that, 物主代词]+ 名词(2),意为“像(1)的(2)”,“(1)般的(2)”。名词(1)和名词(2)也可有复数形式,此时a [an]和that 以及物主代词也要作相应的变动。例如:their Palace of houses (他们的宫殿式的房子)。

大家还能想出什么其他类似的用法都发挥一下想象把!^_^

为下面的代码 每行代码都 添加中文注释 , 每个函数都进行详细注释 , 代码的算法原理也写在注释中 , 原来的英文注释翻译成中文注释 : ```from sentence_transformers.cross_encoder import CrossEncoder # 1. Load a pretrained CrossEncoder model model = CrossEncoder("cross-encoder/stsb-distilroberta-base") # We want to compute the similarity between the query sentence... query = "A man is eating pasta." # ... and all sentences in the corpus corpus = [ "A man is eating food.", "A man is eating a piece of bread.", "The girl is carrying a baby.", "A man is riding a horse.", "A woman is playing violin.", "Two men pushed carts through the woods.", "A man is riding a white horse on an enclosed ground.", "A monkey is playing drums.", "A cheetah is running behind its prey.", ] # 2. We rank all sentences in the corpus for the query ranks = model.rank(query, corpus) # Print the scores print("Query: ", query) for rank in ranks: print(f"{rank['score']:.2f}\t{corpus[rank['corpus_id']]}") """ Query: A man is eating pasta. 0.67 A man is eating food. 0.34 A man is eating a piece of bread. 0.08 A man is riding a horse. 0.07 A man is riding a white horse on an enclosed ground. 0.01 The girl is carrying a baby. 0.01 Two men pushed carts through the woods. 0.01 A monkey is playing drums. 0.01 A woman is playing violin. 0.01 A cheetah is running behind its prey. """ # 3. Alternatively, you can also manually compute the score between two sentences import numpy as np sentence_combinations = [[query, sentence] for sentence in corpus] scores = model.predict(sentence_combinations) # Sort the scores in decreasing order to get the corpus indices ranked_indices = np.argsort(scores)[::-1] print("Scores:", scores) print("Indices:", ranked_indices) """ Scores: [0.6732372, 0.34102544, 0.00542465, 0.07569341, 0.00525378, 0.00536814, 0.06676237, 0.00534825, 0.00516717] Indices: [0 1 3 6 2 5 7 4 8] """```
03-10
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