Adding corpus summary

README.md

@@ -60,3 +60,29 @@ dataset_info:
 ---
 license: cc0-1.0
 ---
+### Dataset Summary
+The collection of MaCoCu parallel corpora have been crawled and consist of pairs of source and target segments (one or several sentences) and additional metadata. The following metadata is included:
+- "src_url" and "trg_url": source and target document URL;
+- "src_text" and "trg_text": text in non-English language and in English Language;
+- "bleualign_score": similarity score as provided by the sentence alignment tool Bleualign (value between 0 and 1);
+- "src_deferred_hash" and "trg_deferred_hash": hash identifier for the corresponding segment;
+- "src_paragraph_id" and "trg_paragraph_id": identifier of the paragraph where the segment appears in the original document;
+- "src_doc_title" and "trg_doc_title": title of the documents from which segments where obtained;
+- "src_crawl_date" and "trg_crawl_date": date and time when source and target documents where donwoaded;
+- "src_file_type" and "trg_file_type": type of the original documents (usually HTML format);
+- "src_boilerplate" and "trg_boilerplate": are source or target segments boilerplates?
+- "bifixer_hash": hash identifier for the segment pair;
+- "bifixer_score": score that indicates how likely are segments to be correct in their corresponding language;
+- "bicleaner_ai_score": score that indicates how likely are segments to be parallel;
+- "biroamer_entities_detected": do any of the segments contain personal information?
+- "dsi": a DSI class (“dsi”): information whether the segment is connected to any of Digital Service Infrastructure (DSI) classes (e.g., cybersecurity, e-health, e-justice, open-data-portal), defined by the Connecting Europe Facility (https://github.com/RikVN/DSI);
+- "translation_direction": translation direction and machine translation identification ("translation-direction"): the source segment in each segment pair was identified by using a probabilistic model (https://github.com/RikVN/TranslationDirection), which also determines if the translation has been produced by a machine-translation system;
+- "en_document_level_variant": the language variant of English (British or American, using a lexicon-based English variety classifier - https://pypi.org/project/abclf/) was identified on document and domain level; 
+- "domain_en": name of the web domain for the English document;
+- "en_domain_level_variant": language variant for English at the level of the web domain.
+
+To load a language pair just indicate the dataset and the pair of languages with English first
+
+```python
+dataset = load_dataset("MaCoCu/parallel_data", "en-is")
+```