Treebanking User-Generated Content: a UD Based Overview of Guidelines, Corpora and Unified Recommendations
Università degli Studi di Cagliari（卡利亚里大学）；Università degli Studi di Torino（都灵大学）；Dublin City University（都柏林城市大学）；University of Stuttgart（斯图加特大学）；Universitat Politècnica de València（瓦伦西亚理工大学）；University of Mannheim（曼海姆大学）；Leibniz-Institut für Deutsche Sprache Mannheim（曼海姆莱布尼茨德语研究所）；INRIA Paris（法国国家信息与自动化研究所巴黎中心）；Georgetown University（乔治城大学）
This article presents a discussion on the main linguistic phenomena which cause difficulties in the analysis of user-generated texts found on the web and in social media, and proposes a set of annotation guidelines for their treatment within the Universal Dependencies (UD) framework of syntactic analysis. Given on the one hand the increasing number of treebanks featuring user-generated content, and its somewhat inconsistent treatment in these resources on the other, the aim of this article is twofold: (1) to provide a condensed, though comprehensive, overview of such treebanks -- based on available literature -- along with their main features and a comparative analysis of their annotation criteria, and (2) to propose a set of tentative UD-based annotation guidelines, to promote consistent treatment of the particular phenomena found in these types of texts. The overarching goal of this article is to provide a common framework for researchers interested in developing similar resources in UD, thus promoting cross-linguistic consistency, which is a principle that has always been central to the spirit of UD.
Fondazione Bruno Kessler（布鲁诺·凯斯勒基金会）；University of Trento（特伦托大学）；Zoom Video Communications（Zoom视频通讯公司）
Speech translation for subtitling (SubST) is the task of automatically translating speech data into well-formed subtitles by inserting subtitle breaks compliant to specific displaying guidelines. Similar to speech translation (ST), model training requires parallel data comprising audio inputs paired with their textual translations. In SubST, however, the text has to be also annotated with subtitle breaks. So far, this requirement has represented a bottleneck for system development, as confirmed by the dearth of publicly available SubST corpora. To fill this gap, we propose a method to convert …
National University of Singapore（新加坡国立大学）；Koc University（科奇大学）；Rijksuniversiteit Groningen（格罗宁根大学）；Radboud University（拉德堡德大学）；National Institute of Japanese Literature（日本文学研究所）；Birmingham City University（伯明翰城市大学）；Instituto Politécnico Nacional（国立理工学院）；Mersin University（梅尔辛大学）；University of East Anglia（东英吉利大学）；ETH Zürich（苏黎世联邦理工学院）
Despite the importance of understanding causality, corpora addressing causal relations are limited. There is a discrepancy between existing annotation guidelines of event causality and conventional causality corpora that focus more on linguistics. Many guidelines restrict themselves to include only explicit relations or clause-based arguments. Therefore, we propose an annotation schema for event causality that addresses these concerns. We annotated 3,559 event sentences from protest event news with labels on whether it contains causal relations or not. Our corpus is known as the Causal News Co…
Clinical Document Corpora -- Real Ones, Translated and Synthetic Substitutes, and Assorted Domain Proxies: A Survey of Diversity in Corpus Design, with Focus on German Text Data
Institute for Medical Informatics, Statistics and Epidemiology (IMISE), University of Leipzig（莱比锡大学医学信息学、统计学与流行病学研究所）
Kyoto University（京都大学）；National Institute of Information and Communications Technology（国立信息与通信技术研究所）
Lectures translation is a case of spoken language translation and there is a lack of publicly available parallel corpora for this purpose. To address this, we examine a language independent framework for parallel corpus mining which is a quick and effective way to mine a parallel corpus from publicly available lectures at Coursera. Our approach determines sentence alignments, relying on machine translation and cosine similarity over continuous-space sentence representations. We also show how to use the resulting corpora in a multistage fine-tuning based domain adaptation for high-quality lectu…
Hochschule für Technik und Wirtschaft Berlin（柏林工程与经济应用技术大学）；Alice Salomon Hochschule Berlin（柏林爱丽丝·萨洛蒙应用科学大学）
Over the course of the COVID-19 pandemic, existing conspiracy theories were refreshed and new ones were created, often interwoven with antisemitic narratives, stereotypes and codes. The sheer volume of antisemitic and conspiracy theory content on the Internet makes data-driven algorithmic approaches essential for anti-discrimination organizations and researchers alike. However, the manifestation and dissemination of these two interrelated phenomena is still quite under-researched in scholarly empirical research of large text corpora. Algorithmic approaches for the detection and classification …
Hasso Plattner Institute, University of Potsdam（波茨坦大学哈索·普拉特纳研究所）；Friedrich Schiller University Jena（耶拿弗里德里希·席勒大学）；German Cancer Society（德国癌症协会）
The lack of publicly accessible text corpora is a major obstacle for progress in natural language processing. For medical applications, unfortunately, all language communities other than English are low-resourced. In this work, we present GGPONC (German Guideline Program in Oncology NLP Corpus), a freely distributable German language corpus based on clinical practice guidelines for oncology. This corpus is one of the largest ever built from German medical documents. Unlike clinical documents, clinical guidelines do not contain any patient-related information and can therefore be used without d…
New York University Abu Dhabi（纽约大学阿布扎比分校）；University of Bahrain（巴林大学）
Most Arabic natural language processing tools and resources are developed to serve Modern Standard Arabic (MSA), which is the official written language in the Arab World. Some Dialectal Arabic varieties, notably Egyptian Arabic, have received some attention lately and have a growing collection of resources that include annotated corpora and morphological analyzers and taggers. Gulf Arabic, however, lags behind in that respect. In this paper, we present the Gumar Corpus, a large-scale corpus of Gulf Arabic consisting of 110 million words from 1,200 forum novels. We annotate the corpus for sub-d…
Grammarly；University of Mannheim（曼海姆大学）；Dataminr, Inc.（Dataminr公司）
Computational models of argument quality (AQ) have focused primarily on assessing the overall quality or just one specific characteristic of an argument, such as its convincingness or its clarity. However, previous work has claimed that assessment based on theoretical dimensions of argumentation could benefit writers, but developing such models has been limited by the lack of annotated data. In this work, we describe GAQCorpus, the first large, domain-diverse annotated corpus of theory-based AQ. We discuss how we designed the annotation task to reliably collect a large number of judgments with…
University of Massachusetts Amherst（马萨诸塞大学阿默斯特分校）；Brown University（布朗大学）；Google（谷歌）
Large-scale, high-quality corpora are critical for advancing research in coreference resolution. However, existing datasets vary in their definition of coreferences and have been collected via complex and lengthy guidelines that are curated for linguistic experts. These concerns have sparked a growing interest among researchers to curate a unified set of guidelines suitable for annotators with various backgrounds. In this work, we develop a crowdsourcing-friendly coreference annotation methodology, ezCoref, consisting of an annotation tool and an interactive tutorial. We use ezCoref to re-anno…
Instituto Politécnico Nacional (IPN)（国立理工学院）；Centro de Investigación en Computación (CIC)（计算机研究中心）
Hope is characterized as openness of spirit toward the future, a desire, expectation, and wish for something to happen or to be true that remarkably affects human's state of mind, emotions, behaviors, and decisions. Hope is usually associated with concepts of desired expectations and possibility/probability concerning the future. Despite its importance, hope has rarely been studied as a social media analysis task. This paper presents a hope speech dataset that classifies each tweet first into "Hope" and "Not Hope", then into three fine-grained hope categories: "Generalized Hope", "Realistic Ho…
Recognizing non-standard entity types and relations, such as B2B products, product classes and their producers, in news and forum texts is important in application areas such as supply chain monitoring and market research. However, there is a decided lack of annotated corpora and annotation guidelines in this domain. In this work, we present a corpus study, an annotation schema and associated guidelines, for the annotation of product entity and company-product relation mentions. We find that although product mentions are often realized as noun phrases, defining their exact extent is difficult …
RAAMove: A Corpus for Analyzing Moves in Research Article Abstracts
Faculty of Information Technology, Beijing University of Technology（北京工业大学信息技术学院）；School of Computer Science, Beijing Institute of Technology（北京理工大学计算机学院）
University of Birzeit（比尔宰特大学）；American University of Beirut（贝鲁特美国大学）；United Nations（联合国）
This article presents morphologically-annotated Yemeni, Sudanese, Iraqi, and Libyan Arabic dialects Lisan corpora. Lisan features around 1.2 million tokens. We collected the content of the corpora from several social media platforms. The Yemeni corpus (~ 1.05M tokens) was collected automatically from Twitter. The corpora of the other three dialects (~ 50K tokens each) came manually from Facebook and YouTube posts and comments. Thirty five (35) annotators who are native speakers of the target dialects carried out the annotations. The annotators segemented all words in the four corpora into pref…
Can Frontier LLMs Replace Annotators in Biomedical Text Mining? Analyzing Challenges and Exploring Solutions
The University of Tokyo（东京大学）；Graduate School of Frontier Sciences（前沿科学研究生院）；Department of Computational Biology and Medical Sciences（计算生物学与医学科学系）；Database Center for Life Science（生命科学数据库中心）；Joint Support-Center for Data Science Research（数据科学研究联合支持中心）
