Using Spacy instead of Jieba for chinese text segmentation #114
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ahmednasserswe
requested review from
DGaffney,
computermacgyver and
skyemeedan
as code owners
…e with the other dependencies
skyemeedan
reviewed
Oct 11, 2024
| test_text = '''哈里斯同意与特朗普再进行一次美大选辩论''' | ||
| expected = "哈里 里斯 哈里斯 同意 与 特朗普 再 进行 一次 美 大选 辩论" | ||
| self.assertEqual(self.yake_model.run_chinese_segmentation_with_jieba(test_text), expected) | ||
| expected = "哈里斯 同意 与 特朗 普再 进行 一 次 美 大选 辩论" |
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can we add tests with some of the examples I provided where jieba was giving multiple terms?
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The code for switching over looks fine, but I wouldn't want to merge it in yet unless we've done some sort of comparison (perhaps you already did?). We could dump some example text from piyaoba workspace and compare results side by side? Edit: I see there is already a notebook linked on the ticket, so maybe extend that with results for some sample text side by side? |
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CV2-5247-support-yake-keyword-extraction-for-chinese
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Description
Using Spacy instead of Jieba for Chinese text segmentation
Reference: CV2-5247
How has this been tested?
Locally and added unittests
Are there any external dependencies?
Spacy