Update README.md

README.md

@@ -55,7 +55,9 @@ configs:
     path: data/train-*
 ---
 
-# Material Contracts (Exhibit 10) from SEC/EDGAR
+# <span style="color: #2c2c2c">Material Contracts (Exhibit 10) from SEC/EDGAR</span>
+
+*<span style="color: #81b29a">Because sometimes you need 930,120 examples of corporate legalese to train your next model</span>* ☕
 
 ## Table of Contents
 - [Dataset Card Creation Guide](#dataset-card-creation-guide)
@@ -87,112 +89,134 @@ configs:
     - [Citation Information](#citation-information)
     - [Contributions](#contributions)
 
-## Dataset Description
+## <span style="color: #e07a5f">Dataset Description</span>
+
+Ever wondered what happens when you spend countless late nights crawling through SEC filings? You get this <span style="color: #81b29a">**beautifully curated collection**</span> of corporate contracts that'll make your legal AI models significantly smarter (and probably more verbose).
+
+- **<span style="color: #e07a5f">Homepage:</span>** NA *<span style="color: #81b29a">(because who needs sleep when you have datasets?)</span>*
+- **<span style="color: #e07a5f">Repository:</span>** [Crawler](https://github.com/ChenghaoMou/edgar-crawler/tree/main) *<span style="color: #81b29a">(the code that made this madness possible)</span>*
+- **<span style="color: #e07a5f">Paper:</span>** NA *<span style="color: #81b29a">(too busy debugging to write papers)</span>*
+- **<span style="color: #e07a5f">Leaderboard:</span>** NA *<span style="color: #81b29a">(but feel free to create one!)</span>*
+- **<span style="color: #e07a5f">Point of Contact:</span>** mouchenghao at gmail dot com *<span style="color: #81b29a">(caffeine-powered responses guaranteed)</span>*
 
-- **Homepage:** NA
-- **Repository:** [Crawler](https://github.com/ChenghaoMou/edgar-crawler/tree/main)
-- **Paper:** NA
-- **Leaderboard:** NA
-- **Point of Contact:** mouchenghao at gmail dot com
+### <span style="color: #e07a5f">Dataset Summary</span>
 
-### Dataset Summary
+Picture this: <span style="color: #e07a5f">**930,120 material contracts**</span> (Exhibit 10) painstakingly collected from sec.gov's EDGAR database. We're talking about legal agreements spanning from <span style="color: #81b29a">**1994 to January 2024**</span>, sourced from 10-K, 10-Q, and 8-K filings. Think of Exhibit 10 as the treasure trove where companies hide their most important legal paperwork – employment agreements, merger documents, licensing deals, and all those contracts that make corporate lawyers reach for their third espresso.
 
-930120 material contracts (Exhibit 10) collected from sec.gov (EDGAR), specifically from 10-k, 10-Q, and 8-K, ranging from 1994 to Jan 2024. Exhibit 10 consists of a large collection of legal agreements and contracts. 
+This isn't just another dataset – it's <span style="color: #81b29a">**three decades of corporate America's legal DNA**</span>, ready for your next language model to digest.
 
-### Supported Tasks and Leaderboards
+### <span style="color: #e07a5f">Supported Tasks and Leaderboards</span>
 
-- `language-modeling` or `text-generation`: The dataset can be used to build language model in legal/finance domain.
+- <span style="color: #2c2c2c; background-color: #f4f3ee; padding: 2px 4px; border-radius: 3px;">`language-modeling`</span> or <span style="color: #2c2c2c; background-color: #f4f3ee; padding: 2px 4px; border-radius: 3px;">`text-generation`</span>: Perfect for building domain-specific models that understand the intricate dance of legal and financial language. Your model will learn to speak fluent "corporate" – complete with all those delightful <span style="color: #81b29a">*whereases*</span> and <span style="color: #81b29a">*heretofores*</span>.
 
-Currently, there is no leaderboard for this dataset.
+Currently, there's no leaderboard for this dataset, but hey, that's an <span style="color: #e07a5f">**opportunity**</span> waiting for someone with enough coffee and determination!
 
-### Languages
+### <span style="color: #e07a5f">Languages</span>
 
-The primary language is US English with the rare instances of other languages.
+Primarily <span style="color: #81b29a">**US English**</span>, though you might encounter the occasional foreign phrase when companies get international. It's like <span style="color: #81b29a">*linguistic archaeology*</span> – you never know what you'll dig up.
 
-## Dataset Structure
+## <span style="color: #e07a5f">Dataset Structure</span>
 
-### Data Instances
+### <span style="color: #e07a5f">Data Instances</span>
 
-Please refer to the data viewer for examples.
+Check out the data viewer for examples – trust me, it's more interesting than it sounds. Each instance is like a <span style="color: #81b29a">*little corporate story*</span> waiting to be told.
 
-### Data Fields
+### <span style="color: #e07a5f">Data Fields</span>
+
+Here's what each record contains <span style="color: #81b29a">*(because data dictionaries are love letters to future developers)*</span>:
 
 | Field | Description |
 |---|---|
-| `index_html_url` | filing index page |
-| `index_text_url` | filing index text page |
-| `cik` | Central Index Key from EDGAR |
-| `name` | Company name |
-| `type` | filing type |
-| `date` | filing date |
-| `seq` | seq number in in the filing |
-| `desc` | description provided from the filing |
-| `doc_type` | document type (e.g. EX-10) |
-| `size` | document size |
-| `filename` | document name |
-| `file_url` | document page url |
-| `file` | GCS file uri (private) |
-| `__index_level_0__` | please ignore |
-| `file_content` | text content (e.g. html) or base64 string of the binary content (e.g. pdf) |
+| `index_html_url` | Filing index page *(your breadcrumb trail back to the source)* |
+| `index_text_url` | Filing index text page *(for when HTML isn't your thing)* |
+| `cik` | Central Index Key from EDGAR *(think of it as a company's social security number)* |
+| `name` | Company name *(who's responsible for this legal masterpiece)* |
+| `type` | Filing type *(10-K, 10-Q, or 8-K – the holy trinity of SEC filings)* |
+| `date` | Filing date *(when this document saw the light of day)* |
+| `seq` | Sequence number in the filing *(because order matters)* |
+| `desc` | Description provided from the filing *(sometimes helpful, sometimes cryptic)* |
+| `doc_type` | Document type (e.g. EX-10) *(the exhibit classification)* |
+| `size` | Document size *(bigger isn't always better, but it usually means more billable hours)* |
+| `filename` | Document name *(often more creative than you'd expect)* |
+| `file_url` | Document page URL *(your direct line to the source)* |
+| `file` | GCS file URI *(private, like a good secret)* |
+| `__index_level_0__` | Please ignore *(the artifact of data wrangling we all pretend doesn't exist)* |
+| `file_content` | Text content (HTML) or base64 string for binary content (PDF) *(the good stuff)* |
+
+### <span style="color: #e07a5f">Data Splits</span>
+
+There's no split by design – everything lives under <span style="color: #2c2c2c; background-color: #f4f3ee; padding: 2px 4px; border-radius: 3px;">`train`</span> because sometimes life is simpler that way. Feel free to create your own splits based on your specific needs <span style="color: #81b29a">*(and caffeine levels)*</span>.
 
-### Data Splits
+## <span style="color: #e07a5f">Dataset Creation</span>
 
-The dataset does not have a split by design. Everything is under `train` by convention.
+### <span style="color: #e07a5f">Curation Rationale</span>
 
-## Dataset Creation
+Why spend <span style="color: #e07a5f">**sleepless nights**</span> building this dataset? Because SEC EDGAR is a <span style="color: #81b29a">**goldmine**</span> of publicly available corporate intelligence, and someone had to do the heavy lifting of making it ML-ready. This collection of exhibit files gives researchers direct access to the contracts and agreements that drive corporate decision-making – no more parsing through entire filings to find the good stuff.
 
-### Curation Rationale
+### <span style="color: #e07a5f">Source Data</span>
 
+https://www.sec.gov/ *<span style="color: #81b29a">(the government's gift to data scientists everywhere)</span>*
 
-SEC EDGAR is a public available service from which one can query and access corporate filings. This collection of one specific exhibit files enables researchers to learn and model from contracts and agreements directly.
+#### <span style="color: #e07a5f">Initial Data Collection and Normalization</span>
 
+The data collection process was like archaeological excavation, but with more <span style="color: #81b29a">**Python**</span> and less dirt. We crawled through years of filings (10-K, 8-K, and 10-Q), extracting each exhibit individually with complete metadata. It's the kind of methodical, detail-oriented work that requires <span style="color: #e07a5f">multiple monitors</span> and a steady supply of debugging fuel.
 
-### Source Data
+Each document was downloaded with <span style="color: #81b29a">*surgical precision*</span>, preserving all metadata for maximum research utility. Think of it as digital preservation, but for corporate paperwork.
 
-https://www.sec.gov/
+#### <span style="color: #e07a5f">Who are the source language producers?</span>
 
-#### Initial Data Collection and Normalization
+The unsung heroes behind this dataset are the army of <span style="color: #81b29a">**finance professionals, lawyers, and corporate executives**</span> who craft these documents. The SEC requires public companies, insiders, and broker-dealers to file these periodic statements, creating a continuous stream of corporate communication that investors and researchers rely on for informed decision-making.
 
+These documents represent the <span style="color: #81b29a">*collective voice of corporate America*</span> – sometimes eloquent, sometimes bureaucratic, always fascinating from a linguistic perspective.
 
-The data is collected by year from all filings that are 10-K, 8-K, or 10-Q. Each exhibit is individually downloaded with all metadata information for maximum completeness. 
+### Annotations
 
+#### Annotation process
 
-#### Who are the source language producers?
+No additional annotations were added – we kept it pure and unadulterated, just the way the SEC intended.
 
-The Securities and Exchange Commission (SEC) requires public companies, certain company insiders, and broker-dealers to file periodic financial statements and other disclosures. Finance professionals and investors rely on SEC filings to make informed decisions when evaluating whether to invest in a company. SEC filings can be accessed for free at EDGAR, the commission's online database. 
+#### Who are the annotators?
+
+The original authors and their legal teams. Every comma placement was probably billable.
 
 ### Personal and Sensitive Information
 
-It might contain PII information (names, emails, job titles, companies) that are already public.
+Fair warning: this dataset might contain PII (names, emails, job titles, companies) that's already in the public domain. It comes with the territory when dealing with public filings – executives' names and contact information are part of the transparency requirements.
+
+## <span style="color: #e07a5f">Considerations for Using the Data</span>
+
+### <span style="color: #e07a5f">Social Impact of Dataset</span>
 
-## Considerations for Using the Data
+This dataset could be the catalyst for <span style="color: #81b29a">**better legal and finance language modeling capabilities**</span>. Imagine AI systems that can parse complex contracts, identify key terms, or help democratize access to legal understanding. Of course, with great power comes great responsibility – <span style="color: #e07a5f">*use it wisely*</span>.
 
-### Social Impact of Dataset
+### <span style="color: #e07a5f">Discussion of Biases</span>
 
-This dataset could enable a better legal and finance language modeling capability.
+Given the source and language, this dataset has a distinctly <span style="color: #81b29a">**US-centric flavor**</span> with a heavy dose of corporate legalese. It reflects the linguistic patterns and legal frameworks of American business culture, which might not translate well to other jurisdictions or informal contexts. Your model might end up sounding like it went to law school <span style="color: #81b29a">*(and accumulated the corresponding debt)*</span>.
 
-### Discussion of Biases
+### <span style="color: #e07a5f">Other Known Limitations</span>
 
-Considering the source and language, it might produce overly US-centric legalese.
+Like any dataset scraped from the wild, this one has its quirks. PDF-to-text conversion isn't perfect, OCR sometimes gets <span style="color: #81b29a">*creative*</span>, and legal documents have their own special way of torturing the English language. Approach with realistic expectations and a <span style="color: #e07a5f">**good debugger**</span>.
 
-### Other Known Limitations
+## <span style="color: #e07a5f">Additional Information</span>
 
-NA
+### <span style="color: #e07a5f">Dataset Curators</span>
 
-## Additional Information
+@chenghao *<span style="color: #81b29a">(the sleep-deprived soul who made this possible)</span>*
 
-### Dataset Curators
+### <span style="color: #e07a5f">Licensing Information</span>
 
-@chenghao
+[Attribution-ShareAlike 4.0 International](https://creativecommons.org/licenses/by-sa/4.0/) *<span style="color: #81b29a">(share and share alike, just the way open source should be)</span>*
 
-### Licensing Information
+### <span style="color: #e07a5f">Citation Information</span>
 
-[Attribution-ShareAlike 4.0 International](https://creativecommons.org/licenses/by-sa/4.0/)
+NA *<span style="color: #81b29a">(but feel free to give credit where credit is due)</span>*
 
-### Citation Information
+### <span style="color: #e07a5f">Contributions</span>
 
-NA
+This dataset exists thanks to countless hours of <span style="color: #e07a5f">**debugging**</span>, data wrangling, and the unwavering belief that good datasets make the world a better place. Special thanks to the SEC for maintaining EDGAR and making corporate transparency possible.
+
+---
 
-### Contributions
+*<span style="color: #81b29a">Happy modeling! May your training runs be swift and your validation losses ever-decreasing.</span>* 🚀
 
-NA
+**<span style="color: #e07a5f">sleepless</span><span style="color: #2c2c2c">@debugging:</span><span style="color: #81b29a">/datasets</span><span style="color: #2c2c2c">$</span> <span style="color: #e07a5f">█</span>**