17 citations · 91 across the 24 of their papers we have counts for
25 papers · 1 filter
The Multilingual FrameNet Corpus
Beatrice Fiumanò, Nicolas Lazzari, Simone Paolo Ponzetto +1
This paper introduces the Multilingual FrameNet Corpus (mFNC), a novel resource that extends the English Berkeley FrameNet corpus by collecting and harmonizing existing language-sp…
On Cross-Lingual Retrieval with Multilingual Text Encoders
Robert Litschko, Ivan Vulić, Simone Paolo Ponzetto +1
In this work we present a systematic empirical study focused on the suitability of the state-of-the-art multilingual encoders for cross-lingual document and sentence retrieval task…
Diachronic Analysis of German Parliamentary Proceedings: Ideological Shifts through the Lens of Political Biases
Tobias Walter, Celina Kirschner, Steffen Eger +3
We analyze bias in historical corpora as encoded in diachronic distributional semantic models by focusing on two specific forms of bias, namely a political (i.e., anti-communism) a…
DebIE: A Platform for Implicit and Explicit Debiasing of Word Embedding Spaces
Niklas Friedrich, Anne Lauscher, Simone Paolo Ponzetto +1
Recent research efforts in NLP have demonstrated that distributional word vector spaces often encode stereotypical human biases, such as racism and sexism. With word representation…
FakeFlow: Fake News Detection by Modeling the Flow of Affective Information
Bilal Ghanem, Simone Paolo Ponzetto, Paolo Rosso +1
Fake news articles often stir the readers' attention by means of emotional appeals that arouse their feelings. Unlike in short news texts, authors of longer articles can exploit su…
Evaluating Multilingual Text Encoders for Unsupervised Cross-Lingual Retrieval
Robert Litschko, Ivan Vulić, Simone Paolo Ponzetto +1
Pretrained multilingual text encoders based on neural Transformer architectures, such as multilingual BERT (mBERT) and XLM, have achieved strong performance on a myriad of language…
AraWEAT: Multidimensional Analysis of Biases in Arabic Word Embeddings
Anne Lauscher, Rafik Takieddin, Simone Paolo Ponzetto +1
Recent work has shown that distributional word vector spaces often encode human biases like sexism or racism. In this work, we conduct an extensive analysis of biases in Arabic wor…
Word Sense Disambiguation for 158 Languages using Word Embeddings Only
Varvara Logacheva, Denis Teslenko, Artem Shelmanov +7
Disambiguation of word senses in context is easy for humans, but is a major challenge for automatic approaches. Sophisticated supervised and knowledge-based models were developed t…
FacTweet: Profiling Fake News Twitter Accounts
Bilal Ghanem, Simone Paolo Ponzetto, Paolo Rosso
We present an approach to detect fake news in Twitter at the account level using a neural recurrent model and a variety of different semantic and stylistic features. Our method ext…
A General Framework for Implicit and Explicit Debiasing of Distributional Word Vector Spaces
Anne Lauscher, Goran Glavaš, Simone Paolo Ponzetto +1
Distributional word vectors have recently been shown to encode many of the human biases, most notably gender and racial biases, and models for attenuating such biases have conseque…
Unmasking Bias in News
Javier Sánchez-Junquera, Paolo Rosso, Manuel Montes-y-Gómez +1
We present experiments on detecting hyperpartisanship in news using a 'masking' method that allows us to assess the role of style vs. content for the task at hand. Our results corr…
HHMM at SemEval-2019 Task 2: Unsupervised Frame Induction using Contextualized Word Embeddings
Saba Anwar, Dmitry Ustalov, Nikolay Arefyev +3
We present our system for semantic frame induction that showed the best performance in Subtask B.1 and finished as the runner-up in Subtask A of the SemEval 2019 Task 2 on unsuperv…
Political Text Scaling Meets Computational Semantics
Federico Nanni, Goran Glavas, Ines Rehbein +2
During the last fifteen years, automatic text scaling has become one of the key tools of the Text as Data community in political science. Prominent text scaling algorithms, however…
Event-based Access to Historical Italian War Memoirs
Marco Rovera, Federico Nanni, Simone Paolo Ponzetto
The progressive digitization of historical archives provides new, often domain specific, textual resources that report on facts and events which have happened in the past; among th…
Unsupervised Sense-Aware Hypernymy Extraction
Dmitry Ustalov, Alexander Panchenko, Chris Biemann +1
In this paper, we show how unsupervised sense representations can be used to improve hypernymy extraction. We present a method for extracting disambiguated hypernymy relationships…
Watset: Local-Global Graph Clustering with Applications in Sense and Frame Induction
Dmitry Ustalov, Alexander Panchenko, Chris Biemann +1
We present a detailed theoretical and computational analysis of the Watset meta-algorithm for fuzzy graph clustering, which has been found to be widely applicable in a variety of d…
Unsupervised Semantic Frame Induction using Triclustering
Dmitry Ustalov, Alexander Panchenko, Andrei Kutuzov +2
We use dependency triples automatically extracted from a Web-scale corpus to perform unsupervised semantic frame induction. We cast the frame induction problem as a triclustering p…
Unsupervised Cross-Lingual Information Retrieval using Monolingual Data Only
Robert Litschko, Goran Glavaš, Simone Paolo Ponzetto +1
We propose a fully unsupervised framework for ad-hoc cross-lingual information retrieval (CLIR) which requires no bilingual data at all. The framework leverages shared cross-lingua…
An Unsupervised Word Sense Disambiguation System for Under-Resourced Languages
Dmitry Ustalov, Denis Teslenko, Alexander Panchenko +3
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 resp…
Enriching Frame Representations with Distributionally Induced Senses
Stefano Faralli, Alexander Panchenko, Chris Biemann +1
We introduce a new lexical resource that enriches the Framester knowledge graph, which links Framnet, WordNet, VerbNet and other resources, with semantic features from text corpora…
A Resource-Light Method for Cross-Lingual Semantic Textual Similarity
Goran Glavaš, Marc Franco-Salvador, Simone Paolo Ponzetto +1
Recognizing semantically similar sentences or paragraphs across languages is beneficial for many tasks, ranging from cross-lingual information retrieval and plagiarism detection to…
A Framework for Enriching Lexical Semantic Resources with Distributional Semantics
Chris Biemann, Stefano Faralli, Alexander Panchenko +1
We present an approach to combining distributional semantic representations induced from text corpora with manually constructed lexical-semantic networks. While both kinds of seman…
Improving Hypernymy Extraction with Distributional Semantic Classes
Alexander Panchenko, Dmitry Ustalov, Stefano Faralli +2
In this paper, we show how distributionally-induced semantic classes can be helpful for extracting hypernyms. We present methods for inducing sense-aware semantic classes using dis…
Building a Web-Scale Dependency-Parsed Corpus from CommonCrawl
Alexander Panchenko, Eugen Ruppert, Stefano Faralli +2
We present DepCC, the largest-to-date linguistically analyzed corpus in English including 365 million documents, composed of 252 billion tokens and 7.5 billion of named entity occu…