MaiBaam Annotation Guidelines
- URL: http://arxiv.org/abs/2403.05902v2
- Date: Fri, 18 Oct 2024 09:39:14 GMT
- Title: MaiBaam Annotation Guidelines
- Abstract summary: This document provides the annotation guidelines for MaiBaam, a Bavarian corpus manually annotated with part-of-speech (POS) tags, syntactic dependencies, and German lemmas.
MaiBaam belongs to the Universal Dependencies (UD) project, and our annotations elaborate on the general and German UD version 2 guidelines.
- Score: 21.10847426724405
- License: http://creativecommons.org/licenses/by-sa/4.0/
- Abstract: This document provides the annotation guidelines for MaiBaam, a Bavarian corpus manually annotated with part-of-speech (POS) tags, syntactic dependencies, and German lemmas. MaiBaam belongs to the Universal Dependencies (UD) project, and our annotations elaborate on the general and German UD version 2 guidelines. In this document, we detail how to preprocess and tokenize Bavarian data, provide an overview of the POS tags and dependencies we use, explain annotation decisions that would also apply to closely related languages like German, and lastly we introduce and motivate decisions that are specific to Bavarian grammar.
Related papers
- A French Corpus Annotated for Multiword Expressions with Adverbial Function [0.0]
This paper presents a French corpus annotated for multiword expressions (MWEs) with adverbial function.<n>We delimit which kind of MWEs we annotated, we describe the resources and methods we used for the annotation, and we briefly comment the results.
arXiv Detail & Related papers (2026-06-03T12:50:25Z) - Bundesrecht: An Open Library and Corpus for German Statutory Reference Processing [16.021243861778846]
bundesrecht is an open resource for German statutory reference processing.<n>It consists of a software library and a structured corpus of German federal law.<n>The library parses, normalizes, and resolves German statutory references.
arXiv Detail & Related papers (2026-05-29T14:18:16Z) - Lost in Translation, Found in Context: Sign Language Translation with Contextual Cues [56.038123093599815]
Our objective is to translate continuous sign language into spoken language text.
We incorporate additional contextual cues together with the signing video.
We show that our contextual approach significantly enhances the quality of the translations.
arXiv Detail & Related papers (2025-01-16T18:59:03Z) - MaiBaam: A Multi-Dialectal Bavarian Universal Dependency Treebank [56.810282574817414]
We present the first multi-dialect Bavarian treebank (MaiBaam) manually annotated with part-of-speech and syntactic dependency information in Universal Dependencies (UD)
We highlight the morphosyntactic differences between the closely-related Bavarian and German and showcase the rich variability of speakers' orthographies.
Our corpus includes 15k tokens, covering dialects from all Bavarian-speaking areas spanning three countries.
arXiv Detail & Related papers (2024-03-15T13:33:10Z) - FRACAS: A FRench Annotated Corpus of Attribution relations in newS [0.0]
We present a manually annotated corpus of 1676 newswire texts in French for quotation extraction and source attribution.
We first describe the composition of our corpus and the choices that were made in selecting the data.
We then detail our inter-annotator agreement between the 8 annotators who worked on manual labelling.
arXiv Detail & Related papers (2023-09-19T13:19:54Z) - Quotations, Coreference Resolution, and Sentiment Annotations in
Croatian News Articles: An Exploratory Study [0.0]
The paper focuses on the annotation of the quotation, co-reference resolution, and sentiment annotation in SETimes news corpus in Croatian.
The generated corpus with quotation features annotations can be used for multiple tasks in the field of Natural Language Processing.
arXiv Detail & Related papers (2022-12-14T11:54:12Z) - Multilingual Word Sense Disambiguation with Unified Sense Representation [55.3061179361177]
We propose building knowledge and supervised-based Multilingual Word Sense Disambiguation (MWSD) systems.
We build unified sense representations for multiple languages and address the annotation scarcity problem for MWSD by transferring annotations from rich-sourced languages to poorer ones.
Evaluations of SemEval-13 and SemEval-15 datasets demonstrate the effectiveness of our methodology.
arXiv Detail & Related papers (2022-10-14T01:24:03Z) - Discourse Analysis via Questions and Answers: Parsing Dependency
Structures of Questions Under Discussion [57.43781399856913]
This work adopts the linguistic framework of Questions Under Discussion (QUD) for discourse analysis.
We characterize relationships between sentences as free-form questions, in contrast to exhaustive fine-grained questions.
We develop the first-of-its-kind QUD that derives a dependency structure of questions over full documents.
arXiv Detail & Related papers (2022-10-12T03:53:12Z) - Chinese Discourse Annotation Reference Manual [9.367612782346207]
This document provides extensive guidelines and examples for Rhetorical Structure Theory (RST) annotation in Mandarin Chinese.
We first introduce preprocessing steps to prepare data for RST annotation.
Secondly, we discuss syntactic criteria to segment texts into Elementary Discourse Units (EDUs)
Finally, we provide examples to define and distinguish discourse relations in different genres.
arXiv Detail & Related papers (2022-10-11T11:02:42Z) - BERT-Assisted Semantic Annotation Correction for Emotion-Related
Questions [0.0]
We use the BERT neural language model to feed information back into an annotation task in a question-asking game called Emotion Twenty Questions (EMO20Q)
We show this method to be an effective way to assess and revise annotations of textual user data with complex, utterance-level semantic labels.
arXiv Detail & Related papers (2022-04-02T18:00:49Z) - Looking for Clues of Language in Multilingual BERT to Improve
Cross-lingual Generalization [56.87201892585477]
Token embeddings in multilingual BERT (m-BERT) contain both language and semantic information.
We control the output languages of multilingual BERT by manipulating the token embeddings.
arXiv Detail & Related papers (2020-10-20T05:41:35Z) - Automatic Extraction of Rules Governing Morphological Agreement [103.78033184221373]
We develop an automated framework for extracting a first-pass grammatical specification from raw text.
We focus on extracting rules describing agreement, a morphosyntactic phenomenon at the core of the grammars of many of the world's languages.
We apply our framework to all languages included in the Universal Dependencies project, with promising results.
arXiv Detail & Related papers (2020-10-02T18:31:45Z) - A Corpus Study and Annotation Schema for Named Entity Recognition and
Relation Extraction of Business Products [68.26059718611914]
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 due to high boundary ambiguity.
We present a preliminary corpus of English web and social media documents annotated according to the proposed guidelines.
arXiv Detail & Related papers (2020-04-07T11:45:22Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.