## 3 Results  
To validate the lexicon's effectiveness and suitability for the domain, we conduct a thorough analysis and evaluation. This evaluation covers three main areas: lexicon size, acquisition of domain-specific semantic information, and word clustering effectiveness. Figure 4 shows a word cloud, visually depicting the relative importance of each word in the context of emergencies in gas pipeline networks. The figure emphasizes words such as \"construction\", \"operation\", \"pipeline\", \"gas pipe\", \"natural gas\", \" excavation\", and \"excavator\" for their significant domain relevance. The size of the lexicon reflects its coverage to a certain extent. Our research involved a detailed statistical analysis of Chinese words processed at various stages. Considering the importance of specific terms, we selected the top 200 words based on their average TF-IDF values. From a risk inventory, we identified 69 critical risk factors. Additionally, 1414 standard terms were extracted from gas pipeline network-related standards. Our custom-trained model allowed us to enrich the lexicon by adding 3429 synonyms and related terms identified through semantic similarity. After merging and removing duplicates, the final lexicon contained 4646 terms. Since single Chinese characters often fail to convey domain-specific relevance and our model was trained on whole words, we excluded all individual characters. Figure 5 illustrates the word length information within the developed dictionary. Bi-character words make up 54% of the vocabulary, while words longer than two characters account for about 46%. This distribution reflects both the linguistic tendencies of the Chinese language and the specific characteristics of sudden gas pipeline events. In general Chinese usage, bi-character words are predominant. However, in the context of gas pipeline emergencies, terms often extend beyond two characters to describe related equipment and procedural measures, resulting in a significant proportion of multi-character words. Figure 4: Visualization of the lexicon development process for emergency response in gas pipeline networks. (**a**) TF-IDF candidate; (**b**) standards and risk inventory; (**c**) domain lexicon. The data reveal that words consisting of up to four characters dominate the lexicon, while those exceeding six characters comprise 5.4% of the total, as shown in Figure 5. Among the entries, the longest term \" (time for pressure-free cooling inside the welder or after its removal) is often used in welding pipe operations, which are critical for gas pipeline emergencies. The word length distribution within the lexicon reveals distinct patterns specific to gas pipeline emergency scenarios. Notably, shorter words dominate the lexicon, with those consisting of two to four characters being the most prevalent. This trend reflects a preference for concise language in emergency management, where brief terms, commonly used nouns, and verbs are crucial for the rapid and clear communication of key information. Conversely, the frequency of words with five or more characters decreases significantly as word length increases. These longer terms, often representing complex concepts or specialized terminology, appear less frequently but are crucial in certain contexts, particularly when describing intricate technical processes or specific risks. This word length distribution has significant implications for the development and optimization of a gas pipeline emergency lexicon. It suggests that effective communication in emergency scenarios relies heavily on concise, easily understood words, while longer, specialized terms are essential in more complex situations. To enhance emergency response efficiency, future research and applications should focus on ensuring a thorough inclusion of shorter words and improving the understanding and application of longer terms, especially in conveying technical terms and details. Table 4 presents a comparison between the domain-specific dictionary developed in this study and those from comparable works.