AI-generated Standard Essential Patent essentiality analysis outputs for methodology discussion and tool development exchange.
AI 生成之標準必要專利必要性分析成果，用於方法論討論與工具開發交流。
All analysis outputs in this repository are generated by AI (Large Language Models). They do NOT constitute legal opinions, legal advice, or any form of professional counsel.
本倉庫中所有分析成果均由 AI（大型語言模型）生成。其不構成法律意見、法律建議或任何形式之專業諮詢。
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These materials are published solely for the purposes of AI tool development exchange, methodology discussion, and technical research within the IP professional community.
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No attorney-client relationship, consultant-client relationship, or any professional engagement is created by viewing or using these materials.
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The AI-generated analyses may contain errors, hallucinations, or misinterpretations. They have NOT been verified to the standard required for litigation, licensing negotiations, or any legal proceeding.
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Any party relying on these materials for actual legal or business decisions does so entirely at their own risk.
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本資料之發布目的僅限於智慧財產權專業社群內的 AI 工具開發交流、方法論討論與技術研究。
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瀏覽或使用本資料不會建立任何律師—當事人關係、顧問—客戶關係或任何專業委任關係。
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AI 生成之分析可能包含錯誤、幻覺（hallucination）或誤解。其未經達到訴訟、授權談判或任何法律程序所要求之標準的驗證。
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任何基於本資料進行實際法律或商業決策之當事方，須完全自行承擔風險。
This repository contains AI-generated analysis outputs from an SEP (Standard Essential Patent) essentiality checking workflow. The prompt/system instructions that produce these outputs are not included in this repository.
本倉庫包含 SEP（標準必要專利）必要性檢核工作流程產出的 AI 生成分析成果。產出這些成果的提示詞 / 系統指令不包含於本倉庫中。
The purpose is to share and discuss:
分享與討論的目的：
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How AI performs on structured patent-vs-standard mapping tasks
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Where AI analysis is useful as a preliminary screening tool, and where it falls short
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Methodological considerations for integrating LLMs into patent engineering workflows
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The evolving capability boundaries of AI in technical-legal analysis
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AI 在結構化的「專利 vs. 標準」比對任務中的表現
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AI 分析在哪些環節可作為初步篩選工具、在哪些環節力有未逮
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將 LLM 整合進專利工程工作流程的方法論考量
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AI 在技術—法律分析中的能力邊界演進
Each published analysis follows a structured format:
每份公開的分析遵循結構化格式：
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Executive Summary — Bottom-line essentiality verdict (ESSENTIAL / LIKELY ESSENTIAL / PARTIALLY ESSENTIAL / NOT ESSENTIAL) with confidence level
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Claim Chart — Element-by-element mapping between patent claim language and technical standard references, with mapping status for each element
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Dialectical Analysis — Thesis (direct mapping conclusion) → Antithesis (counterarguments from patent holder and implementer perspectives) → Synthesis (pragmatic verdict with known unknowns)
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Strategic Implications — Cui Bono analysis and actionable next steps
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執行摘要 — 必要性底線結論（ESSENTIAL / LIKELY ESSENTIAL / PARTIALLY ESSENTIAL / NOT ESSENTIAL），附信心水準
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Claim Chart — 專利請求項文字與技術標準引用之逐 element 比對，每個 element 標示比對狀態
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辯證分析 — 正題（直接比對結論）→ 反題（專利權人與實施者角度之反駁）→ 合題（含已知未知之務實結論）
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戰略意涵 — Cui Bono 分析與可執行的下一步
The underlying analysis methodology draws from established patent law and SEP practice, including:
底層分析方法論援引既有的專利法與 SEP 實務，包括：
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Claim construction under the Phillips v. AWH Corp. (2005) standard, with intrinsic evidence hierarchy (claim language → other claims → specification → prosecution history)
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Element-by-element mapping against normative (mandatory) provisions of technical standards, distinguishing "shall" from "may"
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Cross-layer analysis — distinguishing between a standard defining a mechanism vs. a standard mandating a specific use of that mechanism
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Normative vs. informative text differentiation in standards documents (ETSI, IEEE, 3GPP)
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依 Phillips v. AWH Corp. (2005) 標準之 Claim construction，遵循 intrinsic evidence 優先順序（請求項文字 → 其他請求項 → 說明書 → 審查歷史）
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針對技術標準之規範性（強制性）條文的逐 element 比對，區分 "shall" 與 "may"
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跨層分析 — 區分「標準定義了某機制」與「標準要求以特定方式使用該機制」
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標準文件（ETSI、IEEE、3GPP）中規範性 vs. 資訊性文本之區分
SEP-essentiality-check-Prompt/
├── README.md
├── reports/ — De-identified analysis reports (v2.0+)
│ 去識別化分析報告（v2.0+）
├── case_studies/ — Judgment-based analysis summaries (planned)
│ 基於判決之分析摘要（規劃中）
└── archive/ — Earlier format outputs (pre-v2.0, historical)
早期格式產出（v2.0 以前，歷史參考）
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❌ The prompt / system instruction used to generate analyses
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❌ Any confidential case information, client data, or privileged materials
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❌ Legal opinions or recommendations for specific disputes
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❌ Validated or litigation-ready claim charts
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❌ 用於生成分析的提示詞 / 系統指令
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❌ 任何機密案件資訊、客戶資料或特權資料
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❌ 針對特定爭議之法律意見或建議
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❌ 經驗證的或可用於訴訟之 claim chart
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Patent engineers and IP professionals exploring AI-augmented workflows
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Researchers studying LLM performance on technical-legal reasoning tasks
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SEP licensing practitioners interested in AI as a preliminary screening tool
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探索 AI 輔助工作流程的專利工程師與智財專業人士
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研究 LLM 在技術—法律推理任務上表現的研究者
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對 AI 作為初步篩選工具有興趣的 SEP 授權從業者
| Version | Date | Description |
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| v0.1 | 2025-07 | Initial single-pass SEP analysis prompt (included in repo as historical reference) |
| v2.0+ | 2026 | Significantly evolved architecture with structured claim construction protocol, multi-tier mapping system, dialectical analysis, and quality control checklist. Outputs from this version are published here; the prompt itself is not public. |
| v2.4 | 2026-03 | Current version. Added Decision Tree verdict (replacing numerical scoring), programmatic search protocol for large standards (>100p), output de-identification, and dual deployment mode (Claude / general LLM). |
| 版本 | 日期 | 說明 |
|---|---|---|
| v0.1 | 2025-07 | 初始單次 SEP 分析提示詞（作為歷史參考收錄於 repo 中） |
| v2.0+ | 2026 | 大幅演進之架構，包含結構化 claim construction 協議、多層級比對系統、辯證分析與品質管控檢核表。本版產出之分析成果公開於此；提示詞本身不公開。 |
| v2.4 | 2026-03 | 現行版本。新增 Decision Tree 判定（取代數字評分）、大型標準文件程式性搜索協議（>100 頁）、輸出去識別化、雙部署模式（Claude / 通用 LLM）。 |
The MIT License applies to the repository structure, README, and any code or scripts. The AI-generated analysis outputs are provided "as-is" under the same license with the additional disclaimer stated above.
MIT 授權適用於倉庫結構、README 及任何程式碼或腳本。AI 生成之分析成果以相同授權「按現狀」提供，並附加上述免責聲明。
CamusTsai — IP professional with 15+ years of experience in patent litigation and SEP/FRAND licensing. Exploring AI-augmented patent analysis workflows with structured LLM cognitive architectures.
CamusTsai — 擁有 15 年以上專利訴訟與 SEP/FRAND 授權經驗之智慧財產權專業人士。以結構化 LLM 認知架構探索 AI 輔助專利分析工作流程。