Creating Domain-Specific Chinese Glossaries From Source Texts
The reader can build Chinese glossaries for specific domains by extracting terms from real documents, defining them from context, and organizing them for reuse.
Why this article matters
A domain glossary is not a vocabulary dump. It is a tool for reading a real set of texts: contracts, product pages, hospital forms, app policies, research papers, standards, job ads, menus, or transcripts. The goal is reuse, not collection.
Glossary field map
| Field | Why it matters |
|---|---|
| Term | Chinese form, including variants/abbreviations. |
| Pinyin | Only when pronunciation matters or is uncertain. |
| Definition | Plain-language meaning in this domain. |
| Source sentence | Prevents false abstraction. |
| Domain | Legal, medical, UI, education, logistics, etc. |
| Register | official, technical, colloquial, marketing, platform, etc. |
| Related terms | Builds word families and process maps. |
| Translation | Context-specific, not universal. |
| Confidence | verified, tentative, needs expert review. |
The article
Domain vocabulary is learned best from source texts. If you need to read Chinese job ads, build a job-ad glossary from job ads. If you need Chinese medical forms, build from intake forms and hospital pages. If you need AI infrastructure Chinese, build from product docs, policy texts, and technical explainers. A general word list will not show genre behavior.
Choose sources before choosing terms. A glossary built from random web snippets will be uneven. Better source sets include five product pages from the same category, ten public notices from the same agency type, three contracts of the same genre, or one technical standard plus related manuals. The source set defines the domain.
Term extraction should be selective. Keep repeated terms, technical labels, official field names, unclear compounds, key collocations, abbreviations, and translation-risk terms. Do not include every unknown word. If a word is general and easy to understand from context, it may not belong in the domain glossary.
Definitions should come from context first. Suppose your term is 备案. In one domain it may mean filing/recordation; in another it may be regulatory registration; in an app context it might appear as ICP备案. The glossary entry should say where and how the term functions. A single English gloss is not enough.
Related terms are the hidden power of the glossary. For e-commerce, 售后 connects to 退款, 退货, 换货, 仅退款, 退货退款, 运费险. For legal documents, 义务 connects to 责任, 权利, 违约, 赔偿, 承担. For cloud computing, 部署 connects to 配置, 实例, 镜像, 容器, 监控. The learner should see systems, not isolated labels.
A glossary also needs maintenance. Merge duplicates. Mark outdated terms. Split broad terms into domain-specific entries. Add source examples. Flag region-specific or organization-specific usage. Delete low-value entries that never recur.
Extraction decision tree
Keep a term if it meets at least one condition:
- It appears repeatedly in the source set.
- It labels a field, role, procedure, status, or document section.
- It has a domain-specific meaning not obvious from general Chinese.
- It is a collocation needed for reading the genre.
- It creates translation risk.
- It belongs to a process map.
Worked example: app privacy glossary
| Term | Domain definition | Related terms |
|---|---|---|
| 个人信息 | Information relating to identifiable individuals | 敏感个人信息, 处理, 收集 |
| 处理 | Collection/use/storage/sharing/deletion etc. in privacy context | 收集, 使用, 共享, 删除 |
| 授权 | User permission/authorization | 同意, 拒绝, 撤回 |
| 出境 | Cross-border transfer/export of personal information | 境外接收方, 安全评估 |
Learner traps and repairs
| Trap | Why it hurts | Better habit |
|---|---|---|
| Adding every unknown word | Glossary becomes unusable. | Extract terms with domain value. |
| Using universal translations | Domain meanings vary. | Define in source context. |
| No source sentence | Later you cannot verify usage. | Save one real sentence. |
| No confidence label | Tentative guesses look final. | Mark verified/tentative/expert-needed. |
| Ignoring related terms | You learn labels but not systems. | Build process maps. |
Practice protocol
Choose a source set of 5–10 texts in one domain. Extract 30 candidate terms. Cut to 15. For each, add source sentence, domain definition, related terms, and confidence. Review the glossary by reading a new text in the same domain.
Additional practice and repair
Glossary diagnostics
| Bad glossary habit | Why it fails | Repair |
|---|---|---|
| Adding every unknown word | Glossary becomes unreadable. | Add repeated, domain-critical, or translation-risk terms. |
| One English equivalent only | Domain terms rarely map one-to-one. | Include definition, source sentence, and confidence. |
| No source trace | Terms lose register and authority. | Save source title, URL/file, date, and document type. |
| Mixing domains | Meanings blur across law, medicine, tech, policy. | Tag domain and subdomain. |
| Never retiring entries | Low-value terms clutter review. | Merge, archive, or delete. |
Entry template upgrade
| Field | Requirement |
|---|---|
| Term | Chinese form; include variants/abbreviations if relevant. |
| Pinyin | Useful for oral review, not a substitute for examples. |
| Plain definition | Define in the project’s context. |
| Source sentence | Preserve enough context to prove usage. |
| Domain/register | Legal, medical, AI, e-commerce, public notice, etc. |
| Related terms | Opposites, parent category, near-synonyms, abbreviations. |
| Translation | Provisional, final, or do-not-translate. |
| Confidence | Low/medium/high with reason. |
Before/after repair set
| Weak entry | Strong entry |
|---|---|
| 算力 = computing power | 算力: computing capacity in AI/cloud policy/product texts; collocates 算力基础设施, 算力需求, 算力中心. Confidence medium; verify by source. |
| 风控 = risk control | 风控: fintech/platform risk-control system/process; not generic “be careful.” Related 反洗钱, 实名认证, 可疑交易. |
| 结项 = finish | 结项: formal grant/project closure after review/acceptance, not ordinary ending. |
The glossary builder should support duplicate detection, source snippets, confidence levels, domain tags, variant forms, and export to reading tools or flashcards. Add a “translation risk” flag for terms that look easy but are domain-specific.
Practice visualization
Build a glossary-builder template with import, extraction, tagging, definition, source sentence, related-term graph, review, and export stages. Include warning flags for terms with high translation risk.
Check workflow claims against translation/glossary documentation and domain-terminology practices. Make clear that glossary building improves reading, not professional qualification in a domain.
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