Despite many recent papers on Arabic Named Entity Recognition (NER) in the news domain, little work has been done on microblog NER. NER on microblogs presents many complications such as informality of language, shortened named entities, brevity of expressions, and inconsistent capitalization (for...
An Arabic twitter data set of 7,503 tweets. The released data contains manual Sentiment Analysis annotations as well as automatically extracted features, saved in Comma Separated (CSV) and Attribute-Relation File Format (ARFF) file formats. Due to twitter privacy restrictions we replaced the orig...
Automatically generated corpus of 98,818 graph/string pairs.
A burst-annotated co-occurrence network about the Arab Spring topic built on the top of New York Times article snapshots from the years 2010-2013.
The corpus contains 1,030 online communication messages, randomly selected from Network News Transfer Protocol (NNTP) newsgroups, the bug tracking system Bugzilla and the bug tracking system GitHub. NNTP articles, Bugzilla and GitHub comments were selected randomly so that the sample exhibits sim...
The AuCoPro-Splitting dataset contains compounds annotated with their compound boundaries and linking morphemes. The dataset consists of two files, one for Afrikaans and one for Dutch. The annotation was performed according to annotation guidelines as described in Verhoeven, van Zaanen, van Huyss...
ACOPOST is a free and open source collection of four part-of-speech taggers (t3, met, tbt, and et). In corpus linguistics, part-of-speech tagging (POS tagging or POST), also called grammatical tagging or word-category disambiguation, is the process of marking up the words in a text (corpus) as co...
MSTParser is a non-projective dependency parser (see McDonald et al., 2005a, 2006) that searches for maximum spanning trees over directed graphs. Models of dependency structure are based on large-margin discriminative training methods (see McDonald et al., 2005b). Projective parsing is also suppo...
TinySVM is an implementation of Support Vector Machines (SVMs) (Vapnik, 1995; Vapnik, 1998) for the problem of pattern recognition.
Treat is a toolkit for natural language processing and computational linguistics in Ruby. The Treat project aims to build a language- and algorithm- agnostic NLP framework for Ruby with support for tasks such as document retrieval, text chunking, segmentation and tokenization, natural language pa...