We initiate by extracting a set of nouns from the responses in data of Oogiri-GO. For this, we employ NLTK [91], Jieba 4,
and Janome 5 for various languages, considering the performance differences of different part-of-speech analysis tools across

4https://github.com/fxsjy/jieba
5https://github.com/mocobeta/janome

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languages.

Specifically, we utilize NLTK, a suite of open source Python modules, data sets, and tutorials supporting research and
development in natural language processing, to extract nouns from English text and the core code snippet is presented below:

1 from nltk import word_tokenize, pos_tag

2
3 def extract_nouns(text):

tokens = word_tokenize(text)
tagged_words = pos_tag(tokens)
conditions = [word for word, pos in tagged_words if pos.startswith(’N’)]
return conditions

For Chinese text, we utilize the widely adopted Chinese segmentation tool, Jieba, for part-of-speech analysis. The core

implementation code is provided below:

1 import jieba.posseg as psg
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