D1.2.1 The HaBiT system v1: First integrated system prototype

Corpus building tools

Software

• WebBootCaT, a search engine querying and corpus building tool. It queries a search engine with user specified words or phrases, obtains URLs of relevant documents fount by the search engine and downloads the documents.
• SpiderLing, a web spider for linguistics — is software for obtaining text from the web useful for building text corpora. Many documents on the web only contain material not suitable for text corpora, such as site navigation, lists of links, lists of products, and other kind of text not comprised of full sentences. In fact such pages represent the vast majority of the web. Therefore, by doing unrestricted web crawls, we typically download a lot of data which gets filtered out during post-processing. This makes the process of web corpus collection inefficient.
• Chared is a tool for detecting the character encoding of a text in a known language. The language of the text has to be specified as an input parameter so that correspondent language model can be used. The package contains models for a wide range of languages. In general, it should be more accurate than character encoding detection algorithms with no language constraints.
• Justext is a tool for removing boilerplate content, such as navigation links, headers, and footers from HTML pages. It is designed to preserve mainly text containing full sentences and it is therefore well suited for creating linguistic resources such as Web corpora. A HTML page is split to paragraphs and a context sensitive heuristic algorithm is employed to separate content from boilerplate.
• Onion is a tool for removing duplicate parts from large collections of texts. One instance of duplicate parts is kept, others are marked or removed. The tool allows removing both identical and similar documents, on any level (document, paragraph, sentence — if present in the data). The de-duplication algorithm is based on comparing hashes of n-grams of words.
• Unitok is a universal text tokeniser with specific settings for many languages. It can turn plain text into a sequence of newline-separated tokens (vertical format), while preserving XML-like tags containing metadata.

Language dependent models

• Language samples for language identification (possibly using a character trigram model):
  • Amharic_v1.txt
  • Arabic_v1.txt
  • English_v1.txt
  • Oromo_v1.txt
  • Somali_v1.txt
  • Tigrinya_v1.txt
• Wordlists for language identification and boilerplate removal:
  • Amharic_v1.wl.txt
  • Arabic_v1.wl.txt
  • English_v1.wl.txt
  • Oromo_v1.wl.txt
  • Somali_v1.wl.txt
  • Tigrinya_v1.wl.txt
• Byte trigram models for character encoding detection:
  • Arabic_v1.edm
  • English_v1.edm
  • Universal_UTF8_v1.edm