You are here
We manually annotated a corpus of 100,000 tokens taken from a collection of English travel writings (both travel reports and guidebooks) about Italy published in the second half of the XIX century and the ’30s of the XX century. The corpus is annotated in BIO format using the tag LOCATION to mark all named entities (including nicknames) referring to: (i) geographical locations; (ii) political locations; (iii) functional locations.
WHAT: a collection of travel writings - non-fictional narratives (reports, diaries, letters) and guidebooks - about Italy written by English native authors and published between the country unification and the beginning of the 30's;
WHY: travel writings can support historical, social, ethnographic, and architectural research but they are also a source of curious information about life in Italy in the past;
We have created a github repository that contains:
- annotation guidelines designed to detect and classify event mentions in texts;
- a corpus of historical texts annotated with events (span + class) following the previously mentioned guidelines.
Due to space limitations, the following resources are in an external Google Drive folder (https://drive.google.com/open?id=1HVIZpCmei90tE2hMWIyH-b7_hhHUKnmb):
This resource contains two datasets. Each dataset consists of pairs of arguments from Nixon's and Kennedy’s speeches related to a topic and annotated with a relation of "attack", "support" or "no_relation".
The release includes the following versions of the dataset:
Full_dataset: A collection of 1907 pairs of arguments by Nixon and Kennedy from the 1960 presidential campaign. Each pair has been manually annotated with a relation of "attack", "support" or "no_relation".
The present resource is about the automatic identification of English-Italian code-mixing in English historical travel writings about Italy. We release:
The Content Types Dataset is a new resource aiming at promoting the analysis of texts as a composition of units with specific semantic and functional roles. By developing this dataset we also introduce a new NLP task for the automatic classification of Content Types. The identification of Content Types may improve the performance of more complex NLP tasks by targeting the portions of the documents that are more relevant.
The current release (February 2017) includes:
SIMPITIKI is a Simplification corpus for Italian and it consists of two sets of simplified pairs: the first one is harvested from the Italian Wikipedia in a semi-automatic way; the second one is manually annotated sentence-by-sentence from documents in the administrative domain.
This resource includes three datasets. Each dataset consists of pairs of snippets related to a topic and annotated as in agreement or disagreement.
The three datasets are:
1960 Elections Dataset : A collection of 350 pairs of snippets (5 blocks of 3 sentences each) by Nixon and Kennedy from the 1960 presidential campaign. Each pair is manually annotated with agreement/disagreement relation, sentiment, and similarity of the solution proposed with respect of the debated topic
QUANDHO (QUestion ANswering Data for italian HistOry) is an Italian question answering dataset created to cover a specific domain, i.e. the history of Italy in the first half of the XX century. This resource is made of: