LatinISE test data for SemEval 2020 task 1 with additional token versions of the corpora

This data collection contains the Latin test data for SemEval 2020 Task 1: Unsupervised Lexical Semantic Change Detection: 

• a Latin text corpus pair (`corpus1/lemma`, `corpus2/lemma`)
• 40 lemmas which have been annotated for their lexical semantic change between the two corpora (`targets.txt`)
• the annotated binary change scores of the targets for subtask 1, and their annotated graded change scores for subtask 2 (`truth/`)

The corpus data have been automatically lemmatized and part-of-speech tagged, and have been partially corrected by hand. For homonyms, the lemmas are followed by the '#' symbol and the number of the homonym according to the Lewis-Short dictionary of Latin when this number is greater than 1. For example, the lemma 'dico' corresponds to the first homonym in the Lewis-Short dictionary and 'dico#2' corresponds to the second homonym, cf. Lewis-Short dictionary.

__Corpus 1__

• based on: LatinISE (McGillivray and Kilgarriff 2013), version on Sketch Engine
• language: Latin
• time covered: from the beginning of the second century before Christ (BC) to the end of the first century BC
• size: ~1.7 million tokens
• format: lemmatized, sentence length >= 2, no punctuation, sentences randomly shuffled
• encoding: UTF-8

__Corpus 2__

• based on: LatinISE (McGillivray and Kilgarriff 2013) , version on Sketch Engine
• language: Latin
• time covered: from the beginning of the first century after Christ (AD) to the end of the twenty-first century AD
• size: ~9.4 million tokens
• format: lemmatized, sentence length >= 2, no punctuation, sentences randomly shuffled
• encoding: UTF-8

Find more information on the data in the papers referenced below.

Besides the official lemma version of the corpora for SemEval-2020 Task 1 we also provide the raw token version (corpus1/token/, corpus2/token/). It contains the raw sentences in the same order as in the lemma version. Find more information on the data and SemEval-2020 Task 1 in the paper referenced below.

The creation of the data was supported by the CRETA center and the CLARIN-D grant funded by the German Ministry for Education and Research (BMBF).

References

Dominik Schlechtweg, Barbara McGillivray, Simon Hengchen, Haim Dubossarsky and Nina Tahmasebi SemEval 2020 Task 1: Unsupervised Lexical Semant