# Dataset: crawl_domain

Languages: en
Multilinguality: monolingual
Size Categories: 10K<n<100K
Annotations Creators: expert-generated

# Dataset Card for Common Crawl Domain Names

### Dataset Summary

Corpus of domain names scraped from Common Crawl and manually annotated to add word boundaries (e.g. "commoncrawl" to "common crawl").

Breaking domain names such as "openresearch" into component words "open" and "research" is important for applications such as Text-to-Speech synthesis and web search. Common Crawl is an open repository of web crawl data that can be accessed and analyzed by anyone. Specifically, we scraped the plaintext (WET) extracts for domain names from URLs that contained diverse letter casing (e.g. "OpenBSD"). Although in the previous example, segmentation is trivial using letter casing, this was not always the case (e.g. "NASA"), so we had to manually annotate the data.

• Text-to-Speech synthesis
• Web search

en: English

## Dataset Structure

### Data Instances

Each sample is an example of space separated segments of a domain name. The examples are stored in their original letter casing, but harder and more interesting examples can be generated by lowercasing the input first.

For example:

Open B S D
NASA
ASAP Workouts

### Data Fields

• example: a string feature: space separated segments of a domain name.

### Data Splits

split size trivial avg_input_length avg_segments
train 17572 13718 12.63 2.65
eval 1953 1536 12.77 2.67
test 2170 1714 12.63 2.66

## Dataset Creation

### Curation Rationale

The dataset was curated by scraping the plaintext (WET) extracts for domain names from URLs that contained diverse letter casing (e.g. "OpenBSD"). Although in the previous example, segmentation is trivial using letter casing, this was not always the case (e.g. "NASA"), so the curators of the dataset had to manually annotate the data.

### Source Data

#### Initial Data Collection and Normalization

Corpus of domain names scraped from Common Crawl and manually annotated to add word boundaries

### Annotations

#### Who are the annotators?

The annotators are the curators of this dataset

## Considerations for Using the Data

### Dataset Curators

The curators of this dataset are Jae Hun Ro and mwurts4google, who are the contributors of the official Github repository for this dataset. Since the account handles of other curators are unknown currently, the authors of the paper linked to this dataset is mentioned here as curators, Hao Zhang, Jae Ro, and Richard Sproat.

### Citation Information

@inproceedings{zrs2020urlsegmentation,
title={Semi-supervised URL Segmentation with Recurrent Neural Networks Pre-trained on Knowledge Graph Entities},
author={Hao Zhang and Jae Ro and Richard William Sproat},
booktitle={The 28th International Conference on Computational Linguistics (COLING 2020)},
year={2020}
}