| --- |
| license: cc-by-nc-4.0 |
| task_categories: |
| - text-generation |
| language: |
| - en |
| tags: |
| - synthetic |
| - synthetic-data |
| - workflow-records |
| - b2b |
| - legal |
| - privacy-safe |
|
|
| size_categories: |
| - 10K<n<100K |
| pretty_name: Ip Copyright Claims |
| --- |
| |
| # Ip Copyright Claims (Synthetic B2B Dataset Preview) |
|
|
| This synthetic workflow dataset simulates **Intellectual Property & Copyright Dispute Claims** for B2B evaluation, internal testing, and prototyping. |
|
|
| ## About this Dataset |
|
|
| The daily pipeline uses AI-assisted research and blueprint review, with deterministic Python rendering for bulk records and local validation before publication. Records are variants of configured workflow scenarios. A larger row count does not establish independent real-world cases or demonstrated model-training performance. |
|
|
| * **Verified record count:** 10,000 |
| * **Privacy-safe:** Contains synthetic names, phone numbers, and company identifiers. |
| * **Structured and checked:** Schema-validated JSONL; inspect the audit for duplicate, content, and similarity-check details. |
| * **Suggested workflow fit:** Law firms and SaaS legal portals training auto-intake bots. |
| * **Category:** Legal |
|
|
| ## Schema Definition |
|
|
| Each record contains the following fields: |
|
|
| * `claim_id` (str): Pre-assigned Claim ID (e.g. IP-COPY-XXXX) |
| * `claimant_name` (str): Pre-assigned Claimant Name |
| * `infringing_party` (str): Pre-assigned Infringing Party Name |
| * `work_description` (str): Summary of copyrighted work (software, media, text) |
| * `infringement_claim` (str): Detailed allegation of copy, reuse, or reverse-engineering |
| * `demand_terms` (str): Specific demands (cease and desist, damages, licensing fees) |
|
|
| --- |
|
|
| ## Get the Commercial Version |
|
|
| For additional synthetic workflow records, the matching private repo is `HaseebDev/ip_copyright_claims-commercial` and is available under a **commercial license**. |
|
|
| * **Payment:** Lemon Squeezy hosted checkout. |
| * **Delivery:** Lemon Squeezy checkout with secure commercial delivery after purchase |
| * **Commercial package:** 100,000 records, schema documentation, and quality audit report. |
|
|
| **[Open the commercial access page](https://haseebdev.github.io/synthetic-data-checkout/commercial-access.html?niche=ip_copyright_claims&demo_repo=HaseebDev%2Fip_copyright_claims&commercial_repo=HaseebDev%2Fip_copyright_claims-commercial&checkout_url=https%3A%2F%2Fsyntheticdatasetlab.lemonsqueezy.com%2Fcheckout%2Fbuy%2F431fde4c-a3ff-4587-825b-7ec496b1e98e%3Fcheckout%255Bcustom%255D%255Bdataset%255D%3Dip_copyright_claims%26checkout%255Bcustom%255D%255Bdemo_repo%255D%3DHaseebDev%252Fip_copyright_claims%26checkout%255Bcustom%255D%255Bcommercial_repo%255D%3DHaseebDev%252Fip_copyright_claims-commercial%26utm_source%3Dhuggingface%26utm_medium%3Ddataset_card%26utm_campaign%3Dip_copyright_claims&commercial_records=100000)** |
|
|
| ## Quality Audit |
|
|
| # Dataset Quality Report |
|
|
| ## Executive Summary |
|
|
| | Metric | Value | |
| | :--- | :--- | |
| | Status | **PASS** | |
| | Quality Score | **94/100** | |
| | Records Audited | 10000 | |
| | Niche | Intellectual Property & Copyright Dispute Claims | |
| | Category | Legal | |
|
|
| ## Quality Gates |
|
|
| | Dimension | Result | |
| | :--- | :--- | |
| | Schema Conformance | 100.0% (10000/10000) | |
| | Duplicate Rows | 0 | |
| | Duplicate Identity Values | 0 | |
| | Non-Synthetic Phone Risk | 0 | |
| | Email Address Count | 0 | |
| | Max Fuzzy Similarity | 0.587 | |
| | Average Words Per Descriptive Field | 98.7 | |
| | Vocabulary Diversity | 0.702 | |
| | Repeated Phrase Count | 15 | |
| | Domain Keyword Coverage | 0.7 | |
|
|
| ## Buyer Assurance |
|
|
| This dataset was checked with deterministic local tooling before publication. The audit verifies schema consistency, uniqueness, text depth, duplicate risk, repeated wording, domain terminology coverage, and obvious PII leakage patterns. |
|
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| All rows receive schema and content checks. Cross-record similarity uses a bounded sample of pairs to keep generation fast; it does not establish that every possible pair is dissimilar. The score measures these automated checks, not downstream model performance or independent medical, legal, or regulatory validation. |
|
|
| ## Findings |
|
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| - **MINOR**: 15 high-frequency non-domain four-word phrase pattern(s) detected. |
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|
|
|
| ## Support |
|
|
| **Add me on Discord: `xomohappy` for access support, delivery questions, or product questions about this premade commercial dataset.** |
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|
