# Dataset Card for "latin_english_parallel"

101k translation pairs between Latin and English, split 99/1/1 as train/test/val. These have been collected roughly 66% from the Loeb Classical Library and 34% from the Vulgate translation. 

For those that were gathered from the Loeb Classical Library, alignment was performd manually between Source and Target sequences. Additionally, the English translations were both 1. copyrighted and 2. outdated. As such, we decided to modernize and transform them into ones that could be used in the public domain, as the original Latin is not copyrighted.
To perform this, we used the gpt3.5-turbo model on OpenAI with the prompt `Translate an old dataset from the 1800s to modern English while preserving the original meaning and exact same sentence structure. Retain extended adjectives, dependent clauses, and punctuation. Output the translation preceded by the text "Modern Translation: ". If a given translation is not a complete sentence, repeat the input sentence. \n'` followed by the source English. 
We then manually corrected all outputs that did not conform to the standard. 


Each sample is annotated with the index and file (and therefore author/work) that the sample is from. If you find errors, please feel free to submit a PR to fix them.

![alt text](distribution.png)
task_categories:translation size_categories:10K<n<100K language:la language:en license:mit region:us
{"language": ["la", "en"], "license": "mit", "size_categories": ["10K<n<100K"], "task_categories": ["translation"], "pretty_name": "Latin to English Translation Pairs", "dataset_info": {"features": [{"name": "id", "dtype": "int64"}, {"name": "la", "dtype": "string"}, {"name": "en", "dtype": "string"}, {"name": "file", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 39252644, "num_examples": 99343}, {"name": "test", "num_bytes": 405056, "num_examples": 1014}, {"name": "valid", "num_bytes": 392886, "num_examples": 1014}], "download_size": 25567350, "dataset_size": 40050586}}
TAGS
#task_categories-translation #size_categories-10K<n<100K #language-Latin #language-English #license-mit #region-us 

# Dataset Card for "latin_english_parallel"

101k translation pairs between Latin and English, split 99/1/1 as train/test/val. These have been collected roughly 66% from the Loeb Classical Library and 34% from the Vulgate translation. 

For those that were gathered from the Loeb Classical Library, alignment was performd manually between Source and Target sequences. Additionally, the English translations were both 1. copyrighted and 2. outdated. As such, we decided to modernize and transform them into ones that could be used in the public domain, as the original Latin is not copyrighted.
To perform this, we used the gpt3.5-turbo model on OpenAI with the prompt 'Translate an old dataset from the 1800s to modern English while preserving the original meaning and exact same sentence structure. Retain extended adjectives, dependent clauses, and punctuation. Output the translation preceded by the text "Modern Translation: ". If a given translation is not a complete sentence, repeat the input sentence. \n'' followed by the source English. 
We then manually corrected all outputs that did not conform to the standard. 


Each sample is annotated with the index and file (and therefore author/work) that the sample is from. If you find errors, please feel free to submit a PR to fix them.

!alt text
# Dataset Card for "latin_english_parallel"

101k translation pairs between Latin and English, split 99/1/1 as train/test/val. These have been collected roughly 66% from the Loeb Classical Library and 34% from the Vulgate translation. 

For those that were gathered from the Loeb Classical Library, alignment was performd manually between Source and Target sequences. Additionally, the English translations were both 1. copyrighted and 2. outdated. As such, we decided to modernize and transform them into ones that could be used in the public domain, as the original Latin is not copyrighted.
To perform this, we used the gpt3.5-turbo model on OpenAI with the prompt 'Translate an old dataset from the 1800s to modern English while preserving the original meaning and exact same sentence structure. Retain extended adjectives, dependent clauses, and punctuation. Output the translation preceded by the text "Modern Translation: ". If a given translation is not a complete sentence, repeat the input sentence. \n'' followed by the source English. 
We then manually corrected all outputs that did not conform to the standard. 


Each sample is annotated with the index and file (and therefore author/work) that the sample is from. If you find errors, please feel free to submit a PR to fix them.

!alt text
TAGS
#task_categories-translation #size_categories-10K<n<100K #language-Latin #language-English #license-mit #region-us 
 # Dataset Card for "latin_english_parallel"

101k translation pairs between Latin and English, split 99/1/1 as train/test/val. These have been collected roughly 66% from the Loeb Classical Library and 34% from the Vulgate translation. 

For those that were gathered from the Loeb Classical Library, alignment was performd manually between Source and Target sequences. Additionally, the English translations were both 1. copyrighted and 2. outdated. As such, we decided to modernize and transform them into ones that could be used in the public domain, as the original Latin is not copyrighted.
To perform this, we used the gpt3.5-turbo model on OpenAI with the prompt 'Translate an old dataset from the 1800s to modern English while preserving the original meaning and exact same sentence structure. Retain extended adjectives, dependent clauses, and punctuation. Output the translation preceded by the text "Modern Translation: ". If a given translation is not a complete sentence, repeat the input sentence. \n'' followed by the source English. 
We then manually corrected all outputs that did not conform to the standard. 


Each sample is annotated with the index and file (and therefore author/work) that the sample is from. If you find errors, please feel free to submit a PR to fix them.

!alt text
passage: TAGS
#task_categories-translation #size_categories-10K<n<100K #language-Latin #language-English #license-mit #region-us 
# Dataset Card for "latin_english_parallel"

101k translation pairs between Latin and English, split 99/1/1 as train/test/val. These have been collected roughly 66% from the Loeb Classical Library and 34% from the Vulgate translation. 

For those that were gathered from the Loeb Classical Library, alignment was performd manually between Source and Target sequences. Additionally, the English translations were both 1. copyrighted and 2. outdated. As such, we decided to modernize and transform them into ones that could be used in the public domain, as the original Latin is not copyrighted.
To perform this, we used the gpt3.5-turbo model on OpenAI with the prompt 'Translate an old dataset from the 1800s to modern English while preserving the original meaning and exact same sentence structure. Retain extended adjectives, dependent clauses, and punctuation. Output the translation preceded by the text "Modern Translation: ". If a given translation is not a complete sentence, repeat the input sentence. \n'' followed by the source English. 
We then manually corrected all outputs that did not conform to the standard. 


Each sample is annotated with the index and file (and therefore author/work) that the sample is from. If you find errors, please feel free to submit a PR to fix them.

!alt text