
Cultivation: I Can Change Probability
修仙:我能改变概率
- Status
- Completed
- Length
- 3.4M Words
- Genre
- Cultivation
- Subgenre
- Fantasy Cultivation
- Updated
- 2y ago
- Source
- Qidian
Stats
705Chapters
0Votes
8kRecs
19.6kFans
Tags
Synopsis
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Reader comments 31
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In fact, if you improve the punctuation marks, the readability will immediately increase significantly. After reading the first few dozen chapters, this is obviously a good book.
Can't stand it. I really can't stand the issue of over-standard symbols. How come the author can't use something as basic as punctuation marks if he doesn't understand them?
I'll change the punctuation carefully, ask the editor to remove the original book, re-list it, and sign a contract. It's no problem. I can earn 1,500 for perfect attendance for a month. If I have better grades, I might earn several thousand yuan.
I've read more than 140 chapters, and I don't want to read anymore. It's such an awesome Golden Finger, and it's in the world of cultivating immortals. You can even say that you can go to alchemy and weapon refining to get a side job, but after building the foundation, it's all about finding materials to build ships, and then building some kind of electromagnetic gun, and then talking about its power. Why is it so big? How big is the space? There are dozens of chapters. In the end, when I encountered a golden elixir monster, I had to lose most of the hull and mount my mount to escape. I really don't understand. Your sect is not here. You have to build a ship with so many precious materials and you can't fly. Can you take it with you? I have a big warehouse filled with so many valuable materials but don't sell them. I really don't know why. I just build ships for the sake of building ships. There is no sense of a main plot. The front is quite nice, so vote for it and support it! Hope it gets better later.
Have you really read anything that can be called a book? Why would someone write a work without even the most basic punctuation marks in the dialogue? Are you really educated? When I first started writing in primary school, my composition teacher taught me to add double quotation marks when writing character dialogues, right?
It was originally well written in the early stages, but as soon as the ship was built, there were a lot of dozens of chapters, all of which were about changing the ship, and I started to lose my mind. I lost all the caution and caution in the past, and it was typical of driving high and driving low.
Putting aside at least half of the manual-like content, the rest is really good. These boring construction instructions are as rare as the punctuation marks, and even more difficult to accept.
I really like the author's novels, but I can't stand the punctuation marks, so I used GPT to compile a pathon code for adding punctuation to Chinese text. Can any programmer help me see if it can be used in novels, so that the author can easily complete the modification of punctuation marks? The following is GPT's reply and code: Yes. The code for adding and correcting punctuation marks may be complicated, but a feasible method is to use natural language processing (NLP) technology to accurately determine the positions of punctuation marks that need to be added and corrected in the text by performing word segmentation, part-of-speech tagging, syntactic analysis and other operations on Chinese novels. The following is a reference code using the Python programming language and Stanford CoreNLP, a popular NLP toolkit: ``` import os from stanfordcorenlp import S tanfordCoreNLP # Set the Stanford CoreNLP server path and port number nlp = StanfordCoreNLP(r'/path/to/stanford-corenlp-full-2020-11-1 7', lang='zh', port=9000) # Read text file with open('novel. Txt', 'r', encoding='utf-8') as f: text = f. Read() # Sentences sentences = nlp. Sent_tokenize(text) # Traverse each sentence, perform word segmentation, part-of-speech tagging and syntactic analysis for sentence in sentences: tokens = nlp. Word_tokenize(sentence) pos_tags = nlp. Pos_tag(sentence) parse_tree = nlp. Parse(sentence) # Correct the position of punctuation marks according to the results of syntactic analysis # Different rules can be written here according to the needs # For example: add a space before all commas, add two spaces after all periods corrected_sentence = pa rse_tree. Replace(',', ' , '). Replace('.', ' . ') # Output the corrected sentence print(corrected_sentence) # Close Stan ford CoreNLP client connection nlp. Close() ``` The above code uses Stanford CoreNLP to perform sentence segmentation, word segmentation, part-of-speech tagging and syntactic analysis of the text, then corrects the punctuation mark position according to the set rules, and outputs each corrected sentence. In actual use, you can modify the rules and output format according to your own needs. At the same time, in order to avoid irreversible impact on the original text, be sure to back up the original text file.
Good guy, group costumes and transformations, the protagonist's cheats are left over from someone else's choice. Are you afraid that your grades will be good?
It poisoned me to death. The protagonist is actually a woman. . . In the category of cultivating immortals, only those who can make fire can have ghosts. . . . .