Articles

Present-day empirical research in computational or theoretical linguistics has at its disposal an enormous wealth in the form of richly annotated and diverse corpus resources. Especially the points of contact between modalities are areas of exciting new research. However, progress in those areas in particular suffers from poor coverage in …...

Data annotation is an important and necessary task for all NLP applications. Designing and implementing a web-based application that enables many annotators to annotate and enter their input into one central database is not a trivial task. These kinds of web-based applications require a consistent and robust backup for the …...

This study undertook a quantitative lexicological analysis using attributed speaker information, and reports on the problems of creating standards when annotating speaker information (gender and age) of conversation sentences in novels. In this paper, we performed a comparative analysis of vocabulary use by gender and age of conversation sentences and …...

We present PDFAnno, a web-based linguistic annotation tool for PDF documents. PDF has become widespread standard for various types of publications, however, current tools for linguistic annotation mostly focus on plain-text documents. PDFAnno offers functions for various types of linguistic annotations directly on PDF, including named entity, dependency relation, and …...

We release a Python module containing several tools to build analogical grids from words contained in a corpus. The module implements several previously presented algorithms. The tools are language-independent. This permits their use with any language and any writing system. We hope that the tools will ease research in morphology …...

This paper describes a pilot study act to investigate the semiotic types of hand gestures in video-recorded speeches and their automatic classification. Gestures, which also comprise e.g. head movements and body posture, contribute to the successful delivery of the message by reinforcing what is expressed by speech or by adding …...

Much has been written regarding the importance of combining visual and textual information to enhance knowledge acquisition (Paivio, 1971, 1986; Mayer & Anderson, 1992). However, the combination of images and text still needs further analysis (Faber, 2012; Prieto, 2008; Prieto & Faber, 2012). An in-depth analysis of the features of …...

This paper introduces a new web-based software tool for annotating text, Text Annotation Graphs, or TAG. It provides functionality for representing complex relationships between words and word phrases that are not available in other software tools, including the ability to define and visualize relationships between the relationships themselves (semantic hypergraphs). …...

The task of Word Sense Disambiguation (WSD) is to determine the meaning of an ambiguous word in a given context. In spite of its importance for most NLP pipelines, WSD can still be seen to be unsolved. The reason is that we currently lack tools for WSD that handle big …...

Standard word embeddings lack the possibility to distinguish senses of a word by projecting them to exactly one vector. This has a negative effect particularly when computing similarity scores between words using standard vector-based similarity measures such as cosine similarity. We argue that minor senses play an important role in …...

In this paper, we present Watasense, an unsupervised system for word sense disambiguation. Given a sentence, the system chooses the most relevant sense of each input word with respect to the semantic similarity between the given sentence and the synset constituting the sense of the target word. Watasense has two …...

In Word Sense Disambiguation, sense annotated corpora are often essential for evaluating a system and also valuable in order to reach a good efficiency. Always created for a specific purpose, there are today a dozen of sense annotated English corpora, in various formats and using different versions of WordNet. The …...

Supervised models for Word Sense Disambiguation (WSD) currently yield to state-of-the-art results in the most popular benchmarks. Despite the recent...

In this study, we investigated unsupervised learning based Korean word sense disambiguation (WSD) using CoreNet, a Korean lexical semantic network. To facilitate the application of WSD to practical natural language processing problems, a reasonable method is required to distinguish between sense candidates. We therefore performed coarse-grained Korean WSD studies while …...

All-words word sense disambiguation (all-words WSD) is the task of identifying the senses of all words in a document. Since the sense of a word depends on the context, such as the surrounding words, similar words are believed to have similar sets of surrounding words. We therefore predict the target …...

In this article, we present details of our corpus of political speeches and introduce using the corpus for metaphor analysis in political discourse. Although specialized corpora on a variety of topics are now easily available, online political corpora available for public use are scarce. The database our research team has …...

This work presents a comparative study between two different approaches to build an automatic classification system for Modality values in the Portuguese language. One approach uses a single multi-class classifier with the full dataset that includes eleven modal verbs; the other builds different classifiers, one for each verb. The performance …...

This paper presents a publicly available corpus of French encyclopedic history texts annotated according to the Berkeley FrameNet formalism. The main difference in our approach compared to previous works on semantic parsing with FrameNet is that we are not interested here in full text parsing but rather on partial parsing. …...

We present in this paper an effort to build an AMR (Abstract Meaning Representation) annotated corpus (a semantic bank) for Brazilian Portuguese. AMR is a recent and prominent meaning representation with good acceptance and several applications in the Natural Language Processing area. Following what has been done for other languages, …...

Representing words as vectors which encode their semantic properties is an important component in natural language processing. Recent advances in distributional semantics have led to the rise of neural network-based models that use unsupervised learning to represent words as dense, distributed vectors, called ‘word embeddings’. These embeddings have led to …...