- Corpora - ELRA lists

CFP: UMR parsing shared task + DMR 2026 workshop
by Dan Zeman 11 Jan '26

11 Jan '26

Call for Participation: Shared Task in Parsing into UMR Please consider participating in shared task in multilingual parsing into Uniform Meaning Representation. Details and registration link here: https://ufal.mff.cuni.cz/umr-parsing The shared task is part of the DMR 2026 workshop, see the call for papers below: Call for Papers: DMR 2026 DMR 2026 invites the submissions of long and short papers about original works on the design, processing, and use of meaning representations. While deep learning methods have led to many breakthroughs in practical natural language applications, there is still a sense among many NLP researchers that we have a long way to go before we can develop systems that can actually “understand” human language and explain the decisions they make. Indeed, “understanding” natural language entails many different human-like capabilities, and they include but are not limited to the ability to track entities in a text, understand the relations between these entities, track events and their participants described in a text, understand how events unfold in time, and distinguish events that have actually happened from events that are planned or intended, are uncertain, or did not happen at all. We believe a critical step in achieving natural language understanding is to design meaning representations for text that have the necessary meaning “ingredients” that help us achieve these capabilities. Such meaning representations can also potentially be used to evaluate the compositional generalization capacity of deep learning models. There has been a growing body of research devoted to the design, annotation, and parsing of meaning representations in recent years. In particular, formal meaning representation frameworks such as Minimal Recursion Semantics (MRS) and Discourse Representation Theory are developed with the goal of supporting logical inference in reasoning-based AI systems and are therefore easily translatable into first-order logic, while other meaning representation frameworks such as Abstract Meaning Representation (AMR), Uniform Meaning Representation (UMR), Tecto-grammatical Representation (TR) in Prague Dependency Treebanks and the Universal Conceptual Cognitive Annotation (UCCA), put more emphasis on the representation of core predicate-argument structure. The automatic parsing of natural language text into these meaning representations and the generation of natural language text from these meaning representations are also very active areas of research, and a wide range of technical approaches and learning methods have been applied to these problems. DMR intends to bring together researchers who are producers and consumers of meaning representations and, through their interaction, gain a deeper understanding of the key elements of meaning representations that are the most valuable to the NLP community. The workshop will provide an opportunity for meaning representation researchers to present new frameworks and to critically examine existing frameworks with the goal of using their findings to inform the design of next-generation meaning representations. One particular goal is to understand the relationship between distributed meaning representations trained on large data sets using network models and the symbolic meaning representations that are carefully designed and annotated by NLP researchers, with an aim of gaining a deeper understanding of areas where each type of meaning representation is the most effective. The workshop solicits papers that address one or more of the following topics: * Development and annotation of meaning representations; * Challenges and techniques in leveraging meaning representations for downstream applications, including neuro-symbolic approaches; * The relationship between symbolic meaning representations and distributed semantic representations; * Issues in applying meaning representations to multilingual settings and lower-resourced languages; * Challenges and techniques in automatic parsing of meaning representations; * Challenges and techniques in automatically generating text from meaning representations; * Meaning representation evaluation metrics; * Cross-framework comparison of meaning representations and their formal properties; * Any other topics that address the design, processing, and use of meaning representations. Contact For any questions regarding the workshop, please contact us atdmr.workshop.2026(a)gmail.com.

1 0

Can LLMs Finally Win? The CRAC 2026 Shared Task on Multilingual Coreference Resolution
by Dan Zeman 11 Jan '26

11 Jan '26

* ———————————————————————————— Call for Participation: CRAC 2026 Shared Task on Multilingual Coreference Resolution ———————————————————————————— https://ufal.mff.cuni.cz/corefud/crac26 We are excited to announce the fifth edition of the Shared Task on Multilingual Coreference Resolution! As in the previous edition, where LLMs were not able to dethrone traditional approaches, the upcoming task again primarily focuses on LLMs and challenges their ability to predict coreference across a range of typologically diverse languages. The results will be presented at the CODI-CRAC 2026 workshop, co-located with the ACL 2026 conference in San Diego, USA. System description papers will be published in the proceedings of CODI-CRAC, also available in the ACL anthology. ————————————— Task description ————————————— The task is to identify mentions and cluster them according to their reference to the same entity. Participants may choose between two tracks: 1. LLM track 2. Unconstrained track ————————————— Data ————————————— The Shared Task is based on the upcoming CorefUD 1.4. collection, which comprises datasets with coreference annotation for at least 17 languages. Participants may also choose to compete on only a subset of these languages. ————————————— Timeline (tentative) ————————————— January 16, 2026 - start of the development phase * release of training and development data * evaluation tool available on GitHub * baseline system available at GitHub * development evaluation possible via CodaBench March 4, 2026 - start of the evaluation phase * test evaluation via CodaBench March 18, 2026 (AoE) - end of the evaluation phase April 10, 2026 - submission of system description papers to the CODI-CRAC 2026 workshop July 3/4, 2026 – the CODI-CRAC workshop at ACL ————————————— Participation ————————————— Please let us know by filling in the registration form: https://ufal.mff.cuni.cz/corefud/crac26#llm-registration <https://ufal.mff.cuni.cz/corefud/crac26#llm-registration> ————————————— Organizers ————————————— Michal Novák, Charles University, Czechia Martin Popel, Charles University, Czechia Zdeněk Žabokrtský, Charles University, Czechia Dan Zeman, Charles University, Czechia Anna Nedoluzhko, Charles University, Czechia Milan Straka, Charles University, Czechia Ondřej Pražák, University of West Bohemia, Czechia Miloslav Konopík, University of West Bohemia, Czechia Jakub Sido, University of West Bohemia, Czechia *

1 0

survey on corpora user experience
by varvara.magomedova＠ung.si 11 Jan '26

11 Jan '26

Dear all, I'm collecting data on corpus interface usability to support a standardization proposal. If you use corpora for research or teaching, I'd very much appreciate 5-10 minutes of your time: https://www.1ka.si/a/65063543 The survey covers common frustrations (export limits, query interfaces, metadata gaps) and desired improvements. It is fully anonymous, doesn't even ask how far you are in your academic career. Thanks a lot! Varya Magomedova varvara.magomedova[(a)]ung.si University of Nova Gorica

1 0

MATS AI Safety Summer Fellowship: Apply by Jan. 18
by Eric Dhan 10 Jan '26

10 Jan '26

A quick reminder that applications to the MATS Summer 2026 fellowship cohort are due by January 18. It only takes 1-2 hours to apply! MATS Summer 2026 <https://www.matsprogram.org/apply?utm_source=corpora&utm_medium=&utm_campai…> (June - August) is a 12-week fully-funded research fellowship for aspiring AI alignment, control, security, and governance researchers. Fellows work directly with mentors from Anthropic, Google DeepMind, OpenAI, UK AISI, GovAI, Redwood, METR, Apollo, Goodfire, AIFP, and other top organizations—with housing and office space provided in Berkeley or London. MATS has accelerated 450+ researchers; among alumni who graduated before 2025, 80% now work on AI safety. *Submit your application by Jan. 18!* <https://www.matsprogram.org/apply?utm_source=corpora&utm_medium=&utm_campai…> Please share this opportunity with your networks. We’d love to reach as many people as possible so that we can continue to attract top talent into AI safety. Best, Eric -- Eric Dhan Operations Generalist, MATS <https://www.matsprogram.org/> LinkedIn <https://www.linkedin.com/in/eric-dhan/>

1 0

CFP: StanceNakba 2026 Shared Task (LREC 2026)
by Wajdi Zaghouani 10 Jan '26

10 Jan '26

We are pleased to invite you to participate in StanceNakba 2026, a shared task co-located with LREC 2026 as part of Nakba-NLP 2026: The 2nd International Workshop on Nakba Narratives as Language Resources. The shared task focuses on Actor- and Topic-Aware Stance Detection in polarized social media discourse related to the Palestinian–Israeli conflict. Task Overview * Subtask A (English): Actor-Level Stance Detection Labels: Pro-Palestine | Pro-Israel | Neutral * Subtask B (Arabic): Cross-Topic Stance Detection Labels: Favor | Against | Neither Topics: normalization with Israel and refugee presence in Jordan Dataset & Evaluation * 2,606 manually annotated social media posts * English and Arabic datasets * Primary evaluation metric: Macro-F1 Important Dates * Training data release: January 10, 2026 * System submission deadline: February 17, 2026 * Workshop: May 11–16, 2026 (TBC) Participation in the shared task is free of charge. Please note that at least one member of each participating team must be registered for the conference. Further details, data access, and submission instructions are available on the shared task website: https://marsadlab.github.io/stancenakba/index.html If you have any questions, feel free to contact us at stancenakba(a)gmail.com<mailto:stancenakba@gmail.com>. We warmly encourage you to join us in advancing stance detection research and improving our understanding of polarized online discourse. Kind regards, The StanceNakba 2026 Organizing Team

1 0

CfA: Conference "How does artificial intelligence challenge our traditional understanding of legal reasoning?" August 27-28, 2026, University of St.Gallen
by reto.gubelmann＠uzh.ch 09 Jan '26

09 Jan '26

Dear Colleagues, I would like to draw your attention to a conference that I’m co-organizing. Please find the call for Abstracts below. For further inquiries, please contact the Organizing Committee at: conference-ile(a)unisg.ch. All best, Reto Gubelmann University of Zurich ********************************* CALL FOR ABSTRACTS How does artificial intelligence challenge our traditional understanding of legal reasoning? August 27-28, 2026, University of St. Gallen This international conference invites scholars, practitioners, and Natural Language Processing (NLP) researchers to explore how contemporary Language AI Systems—especially large language models (LLMs) and Deep Learning Methods—reshape fundamental assumptions and methods about legal method, interpretation, and decision-making. Legal practice often presents itself as value-laden, interpretive, and methodologically disciplined. Yet current Language AI predominantly operate through statistical pattern recognition and representation rather than propositional argument. This tension raises pressing questions: Does Language AI merely automate inessential aspects of legal work, or does it reveal that legal reasoning itself has long contained implicit statistical or probabilistic elements? Do machine-generated legal outputs expose hidden (ir)regularities in judicial and administrative practice? And how should legal theory respond when computational systems appear to “mimic” legal judgment without engaging, for all we know, in human-like, propositional reasoning? We especially welcome contributions addressing, but not limited to, the following themes: • Statistical Aspects in Legal Reasoning: What role do probabilistic or statistical considerations already play—implicitly or explicitly—in legal interpretation and decision-making? • AI and the Transformation of Legal Method: Does the rise of generative Language AI undermine traditional conceptions of doctrinal reasoning, hermeneutics, or precedent? • Values, Normativity, and Language: How do values enter legal language, and can AI systems meaningfully represent or operationalize normative commitments? • AI as Mirror or Distortion of Legal Practice: Does AI reveal the latent patterns of legal discourse, contributing to a more objective practice, or does it impose new biases and structures that distort legal meaning? • Epistemic, Democratic, and Ethical Implications: What does the integration of (currently largely private and often closed-sourced) AI into legal institutions (public administration or courts) imply for legitimacy, transparency, and the rule of law? We invite submissions from law, philosophy, NLP, (computational) linguistics, computer science, statistics and related fields. Both theoretical and empirical contributions are welcome. Confirmed Keynote Speakers • Prof. Dr. Christoph Engel, Max Planck Institute, Bonn • Dr. Joel Niklaus, Machine Learning Engineer, Hugging Face Submission Guidelines: Abstract • Scope: 300–500 words • Submission deadline: February 28, 2026, to conference-ile(a)unisg.ch • Form: Anonymized PDF. Please indicate your name, affiliation and contact information in the body of your email • Notification of acceptance: April 2, 2026 Paper and presentation • Paper scope: 3,000 words • Submission deadline: August 14, 2025 • Presentations of 15 minutes, followed by 30 minutes discussion, online presentations are possible Scientific and Organizing Committee • Désirée Klingler, University of St. Gallen • Peter Hongler, University of St. Gallen • Reto Gubelmann, University of Zurich

1 0

Webinar by: Thamar Solorio (Mohamed bin Zayed University of Artificial Intelligence (MBZUAI))
by HiTZ zentroa 09 Jan '26

09 Jan '26

**** We apologize for the multiple copies of this email. In case you are already registered to the next webinar, you do not need to register again. **** Dear colleague, We are happy to announce the next webinar in the Language Technology webinar series organized by The HiTZ Chair of Artificial Intelligence and Language Technology (https://hitz.eus/katedra). We are organizing one seminar every month. Next webinar: Speaker: Thamar Solorio (Mohamed bin Zayed University of Artificial Intelligence (MBZUAI)) Title: A Research Agenda for Low Resource NLP Date: Thursday, January 15, 2026 - 15:00 Summary: Low resource NLP is nowadays an umbrella keyword that covers a wide set of research directions. In this talk I will argue that it is important to carefully present the low resource scenario and distinguish when the languages are truly lacking resources, as opposed to simulating lack of labeled data. I propose to follow a more systematic way to represent work in this space and to question how we approach technology development for these languages. I will also present recent work in my group that contributes to improve language representation by exploring efficient approaches to diverse languages. Bio: Thamar Solorio is a professor of NLP at MBZUAI where she also serves as Vice Provost for Faculty Excellence and Advancement. Her research interests include NLP for low-resource settings and multilingual data, including code-switching and information extraction. More recently, she has been exploring language and vision problems, focusing on developing inclusive NLP. She served two terms as an elected board member of the North American Chapter of the Association of Computational Linguistics (NAACL) and was PC co-chair for NAACL 2019, and recently stepped down from being co-Editor in Chief of the ACL Rolling Review Initiative (ARR). She was the general chair of the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP). Registration: https://www.hitz.eus/webinar_izenematea Upcoming webinars: Henning Wachsmuth (February 5) José Andrés González-López (March 5) Ranjay Krishna (April 16) You can view the videos of previous webinars and the schedule for upcoming webinars here: http://www.hitz.eus/webinars If you cannot attend this seminar, but you want to be informed of the following HiTZ webinars, please complete this registration form instead: http://www.hitz.eus/webinar_info Best wishes, The HiTZ Chair of Artificial Intelligence and Language Technology P.S: HiTZ will not grant any type of certificate for attendance at these webinars.

1 0

Call for Papers: The 1st Workshop on Computational Affective Science
by Roman Klinger 08 Jan '26

08 Jan '26

Call for Papers: The 1st Workshop on Computational Affective Science First Call for Papers: The 1st Workshop on Computational Affective Science (CAS 2026), co-located with the Language Resources and Evaluation Conference (LREC) 2026 in Palma de Mallorca, Spain, May 16. Website: https://casworkshop.github.io/ <https://casworkshop.github.io/> Contact: cas-workshop(a)googlegroups.com We invite submissions to the first Workshop on Computational Affective Science (CAS 2026), co-located with LREC 2026, on research related to the understanding of affect and emotions through language and computation. CAS will accept archival long and short paper submissions, featuring substantial, original, and unpublished research. We also encourage submissions of extended abstracts from researchers in the broader Affective Science community, with up to two pages of content featuring the research background/hypotheses and a description of methods/results. Extended abstracts are non-archival, offering the option for publication and presentation at other conference venues. Motivation Affect refers to the fundamental neural processes that generate and regulate emotions, moods, and feeling states. Affect and emotions are central to how we organize meaning, to our behavior, to our health and well-being, and to our very survival. Despite this, and even though most of us are intimately familiar with emotions in everyday life, there is much we do not know about how emotions work and how they impact our lives. Affective Science is a broad interdisciplinary field that explores these and related questions about affect and emotions. Since language is a powerful mechanism of emotion expression, there is a growing use of language data and advanced natural language processing (NLP) algorithms to shed light on fundamental questions about emotions. The Workshop on Computational Affective Science (CAS) aims to be a dedicated venue for work focused specifically on the link between NLP and affective science. Interdisciplinary Scope The workshop takes an interdisciplinary approach to affective science and aims at bringing together NLP researchers, scientists, and theorists from many research areas, including psychology, sociology,, neuroscience, and philosophy. Although work in sentiment analysis is decades old, this work often proceeds separately and in different fields from research and theory in affective science. Meanwhile, affective scientists in psychology, sociology, neuroscience and philosophy increasingly seek to use linguistic tools to shed light on the nature of emotions, moods, and feeling states. CAS is therefore co-organized by an interdisciplinary group of researchers (spanning NLP and Affective Science) to foment collaboration at this exciting frontier of research. Submissions We invite long and short archival paper submissions, as well as non-archival extended abstracts on a broad range of topics at the intersection of affective science and natural language processing, including but not limited to: 1. The Nature of Affect and Computational Modeling of Emotions Computational experiments that add to our understanding of affect and emotions, including findings relevant to: * theories and nature of emotion * the biology or neuroscience of emotions * appraisal models * dimensional models (valence / arousal / dominance) * models of constructed emotion * cognitive-affective architectures * emotion dynamics (emergence, intensification, decay, transitions) * emotion granularity * emotion regulation * affective embodiment * evolutionary and developmental affect * emotion–cognition interactions These areas are relevant not just to human affect, but may also apply to data animals and artificial agents. 2. Affective Data and Resources Work on compiling and annotating affect-related information in text, speech, facial and bodily expression, and physiological signals (ECG, EEG, GSR, multimodal biosensing), with a focus on text data (monolingual or multilingual) and multimodal data suitable for an NLP venue. Data from underserved languages is especially encouraged. 3. Emotion Recognition, Prediction, and Inference At the instance level: * emotion classification (discrete emotions, dimensional ratings) * emotion intensity estimation * emotion cause detection * context-aware affect inference (culture, situation, social setting) * structured emotion analysis At the aggregate level: * creating emotion arcs * determining broad trends in emotions over time or across locations * tracking emotional responses toward entities of interest (e.g., climate change) * document-level and cross-document emotion analysis * labeling social networks 4. Applications Including but not limited to: * Affect and health, psychopathology, and mental disorders * Affect and behavior/social science (e.g., interpersonal affect, empathy, group-level affect, affect contagion, computational emotion regulation) * Affect and education * Affect and literature/narratives/digital humanities * Affect and commerce 5. Explainability and Interpretability in Computational Affective Models Work aimed at improving the transparency and interpretability of affective systems. This includes understanding how models represent and infer emotions and identifying key cues driving predictions. 6. Ethics, Fairness, Theory Integration, Philosophical Implications * Bias and generalizability of affective systems across demographics * Privacy and ethics in affective data collection * Examining whether automatic NLP systems rely on current and valid theories of affect and emotion * The implications of machines modeling or simulating affect * Societal considerations surrounding affective artificial agents ------------------------------------------------------------------------ Important Dates (tentative): ·Submission deadline:16 Feb 2026 ·Notification of acceptance: 16 March 2026 ·Camera Ready Paper due: 23 March 2026 ·Workshop date: 16 May 2026 Submission Details: We invite submissions for archival long and short papers, as well as non-archival extended abstracts. Archival long and short papers should feature novel and unpublished work relating to the topics detailed above. We also invite submissions of extended abstractsfrom researchers in the broader Affective Science community, with up to two pages of content featuring the research background/hypotheses and a description of methods/results. Extended abstracts are non-archival, offering the option for publication and presentation at other conference venues. Archival Track: ·Long Paper: Consists of up to 8 pages of content, with additional pages for references, limitations, ethical considerations, and appendices. ·Short Paper: Consists of up to 4 pages of content, with additional pages for references, limitations, ethical considerations, and appendices. (When preparing camera ready papers, you will be allowed one extra page to address comments by the reviewers.) Non-Archival Track: ·Extended Abstract: Up to 2 pages. Submission Format: All submissions must use the LREC 2026 template and follow the guidelines found at:https://lrec2026.info/authors-kit/ <https://lrec2026.info/authors-kit/>(Note: extended abstracts can be limited to being 1-2 pages in length). Mandatory Ethics Section:We ask all authors to include a section on Ethical Considerations in their submission, touching on the ethical concerns and broader societal impacts of the work. This discussion section will not count towards the page limit. Submission Site: All submissions must be made through the SoftConf portal. The link to the system will be shared shortly. Additional Details: Website: https://casworkshop.github.io/ <https://casworkshop.github.io/> Attendance: The workshop will follow the attendance policy of the main conference (https://lrec2026.info/registration-policy/ ). Organizers: * Christopher Bagdon, University of Bamberg, Germany * Krishnapriya Vishnubhotla, National Research Council Canada * Kristen A. Lindquist, The Ohio State University, USA * Lyle Ungar, University of Pennsylvania, USA * Roman Klinger, University of Bamberg, Germany * Saif M. Mohammad, National Research Council Canada Contact us at cas-workshop(a)googlegroups.com with any questions.

1 0

Pre-reviewed (ARR) DEADLINE EXTENSION: HEALING Workshop on Health-Related Discourse and Language (EACL 2026)
by murathan.kurfali＠ri.se 08 Jan '26

08 Jan '26

The First International Workshop on Linguistic Analysis for Health (HeaLing’26) We are excited to announce the First Workshop on Linguistic Analysis for Health (HeaLing), co-located with EACL 2026, to be held in Rabat, Morocco, on March 24–29, 2026. 📌 Important Links Workshop Website: https://healing-workshop.github.io Contact: healing-workshop(a)googlegroups.com CFP & Submissions (OpenReview): https://openreview.net/group?id=eacl.org/EACL/2026/Workshop/HeaLing 🗓️ Key Dates (AoE) Tentative Timeline Event Date Direct submission deadline December 19, 2025 (**passed**) Pre-reviewed (ARR) submission deadline January **10**, 2026 Notification of acceptance January 23, 2026 Camera-ready paper due February 3, 2026 Workshop date March 28 (afternoon session) 🧠 Workshop Scope Language-oriented approaches—such as discourse and conversation analysis, narrative medicine, and linguistic ethnography—have long been central to qualitative investigations of how medical knowledge is produced, communicated, and experienced. Today, advances in natural language processing (NLP) and artificial intelligence (AI) offer new possibilities for extending and scaling linguistic approaches across large health-related datasets. The HeaLing workshop invites contributions that integrate qualitative and computational methods to examine how language informs and transforms medicine as a social and scientific practice. A central focus of the workshop is the practical value of interpretive insights derived from language analysis. We welcome researchers from medical humanities, social and historical studies of medicine, and computational language sciences. The workshop will be held as a half-day event at EACL 2026. 🧩 Topics of Interest (include but are not limited to) - Computational + qualitative discourse analysis of clinical, scientific, policy, and other health-related texts (media, guidelines, patient narratives, clinical notes). - Metaphor and framing in illness narratives, public health messaging, and clinical communication. - Narrative medicine, story-centered clinical interventions, and evaluation of their effects. - Historical and contemporary discourse studies of medical epistemologies (how concepts, categories, and expertise are constructed). - Language, power, and inequality: how linguistic framing shapes access, stigma, and policy for marginalized populations. - Methods for responsible use of NLP/LLMs in medical language research (bias, explainability, mixed-methods validation). - Digital humanities approaches: building and interrogating historical corpora, archives, and born-digital records. - Translational impact: case studies showing how interpretive linguistic insights led to concrete changes in practice, education, or policy. 📝 Submission Format and Reviewing Procedure We accept original and unpublished research contributions (including surveys, position, and theory papers) following the ACL format. The ACL Paper Styles are available here: https://github.com/acl-org/acl-style-files (both LaTeX and Word). Long papers: up to 8 pages (+ references) Short papers: up to 4 pages (+ references) Camera-ready versions will be given one additional page to address reviewers’ comments. Papers must be submitted anonymously. We accept submissions either through our own submission page or via the ACL Rolling Review (ARR). All submissions will undergo double-blind peer review by at least three reviewers, with final acceptance decisions made by the workshop organizers. Accepted papers will be published in the workshop proceedings and presented orally or as posters. 👥 Organizing Committee Ylva Söderfeldt, Uppsala University, Sweden Vera Danilova, Uppsala University, Sweden Julia Reed, University of Vienna, Austria Murathan Kurfalı, RISE Research Institutes of Sweden, Sweden Gavin Farrell, University of Padua, Italy

1 0

Second Call for Nominations – The Keith van Rijsbergen (KvR) Award 2026
by Yifei Yuan 08 Jan '26

08 Jan '26

The KvR Award honours outstanding researchers who have advanced the theoretical foundations of Information Retrieval — those whose work has shaped new models, paradigms, or metrics that deepen our understanding of IR. The award was first presented at ECIR 2024 to Prof. Maarten de Rijke (University of Amsterdam). The second KvR Award will be awarded at ECIR 2026 in Delft! 🔹 Eligibility: active IR researchers with ≥10 years since PhD 🔹 Deadline for nominations: 15 January 2026 🔹 Submit nominations via the form provided below Read more about the award, nomination process, and find the form to submit your nominations here: https://lnkd.in/emecdsXm, https://ecir2026.eu/calls/keith-van-rijsbergen-award

1 0

2026

2025

2024

2023

2022

Corpora