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Found 81 papers, 11 papers with code
»textklang« – Towards a Multi-Modal Exploration Platform for German Poetry
We present the steps taken towards an exploration platform for a multi-modal corpus of German lyric poetry from the Romantic era developed in the project »textklang«.
IMSurReal Too: IMS in the Surface Realization Shared Task 2020
We introduce the IMS contribution to the Surface Realization Shared Task 2020.
Applying Occam’s Razor to Transformer-Based Dependency Parsing: What Works, What Doesn’t, and What is Really Necessary
We find that the choice of pre-trained embeddings has by far the greatest impact on parser performance and identify XLM-R as a robust choice across the languages in our study.
Investigating Active Learning Sampling Strategies for Extreme Multi Label Text Classification
Large scale, multi-label text datasets with high numbers of different classes are expensive to annotate, even more so if they deal with domain specific language.
Improving Neural Political Statement Classification with Class Hierarchical Information
Many tasks in text-based computational social science (CSS) involve the classification of political statements into categories based on a domain-specific codebook.
Using Hierarchical Class Structure to Improve Fine-Grained Claim Classification
The analysis of public debates crucially requires the classification of political demands according to hierarchical claim ontologies (e. g. for immigration, a supercategory “Controlling Migration” might have subcategories “Asylum limit” or “Border installations”).
Identifying and Handling Cross-Treebank Inconsistencies in UD: A Pilot Study
The Universal Dependencies treebanks are a still-growing collection of treebanks for a wide range of languages, all annotated with a common inventory of dependency relations.
The DURel Annotation Tool: Human and Computational Measurement of Semantic Proximity, Sense Clusters and Semantic Change
We present the DURel tool that implements the annotation of semantic proximity between uses of words into an online, open source interface.
PoeticTTS -- Controllable Poetry Reading for Literary Studies
Speech synthesis for poetry is challenging due to specific intonation patterns inherent to poetic speech.
Between welcome culture and border fence. A dataset on the European refugee crisis in German newspaper reports
Besides the released resources and the case-study, our contribution is also methodological: we talk the reader through the steps from a newspaper article to a discourse network, demonstrating that there is not just one discourse network for the German migration debate, but multiple ones, depending on the topic of interest (political actors, policy fields, time spans).
Negation-Instance Based Evaluation of End-to-End Negation Resolution
In this paper, we revisit the task of negation resolution, which includes the subtasks of cue detection (e. g. "not", "never") and scope resolution.
Compound or Term Features? Analyzing Salience in Predicting the Difficulty of German Noun Compounds across Domains
Predicting the difficulty of domain-specific vocabulary is an important task towards a better understanding of a domain, and to enhance the communication between lay people and experts.
Modeling Sense Structure in Word Usage Graphs with the Weighted Stochastic Block Model
We suggest to model human-annotated Word Usage Graphs capturing fine-grained semantic proximity distinctions between word uses with a Bayesian formulation of the Weighted Stochastic Block Model, a generative model for random graphs popular in biology, physics and social sciences.
Lexical Semantic Change Discovery
While there is a large amount of research in the field of Lexical Semantic Change Detection, only few approaches go beyond a standard benchmark evaluation of existing models.
Explaining and Improving BERT Performance on Lexical Semantic Change Detection
Type- and token-based embedding architectures are still competing in lexical semantic change detection.
Real-Valued Logics for Typological Universals: Framework and Application
This paper proposes a framework for the expression of typological statements which uses real-valued logics to capture the empirical truth value (truth degree) of a formula on a given data source, e. g. a collection of multilingual treebanks with comparable annotation.
Applying Occam's Razor to Transformer-Based Dependency Parsing: What Works, What Doesn't, and What is Really Necessary
We find that the choice of pre-trained embeddings has by far the greatest impact on parser performance and identify XLM-R as a robust choice across the languages in our study.
Fast and Accurate Non-Projective Dependency Tree Linearization
We propose a graph-based method to tackle the dependency tree linearization task.
Ensemble Self-Training for Low-Resource Languages: Grapheme-to-Phoneme Conversion and Morphological Inflection
We present an iterative data augmentation framework, which trains and searches for an optimal ensemble and simultaneously annotates new training data in a self-training style.
Integrating Graph-Based and Transition-Based Dependency Parsers in the Deep Contextualized Era
Graph-based and transition-based dependency parsers used to have different strengths and weaknesses.
DEbateNet-mig15:Tracing the 2015 Immigration Debate in Germany Over Time
DEbateNet-migr15 is a manually annotated dataset for German which covers the public debate on immigration in 2015.
CCOHA: Clean Corpus of Historical American English
Modelling language change is an increasingly important area of interest within the fields of sociolinguistics and historical linguistics.
GRAIN-S: Manually Annotated Syntax for German Interviews
The dataset extends an existing corpus GRAIN and comes with constituency and dependency trees for six interviews.
IMSurReal: IMS at the Surface Realization Shared Task 2019
We introduce the IMS contribution to the Surface Realization Shared Task 2019.
Head-First Linearization with Tree-Structured Representation
We present a dependency tree linearization model with two novel components: (1) a tree-structured encoder based on bidirectional Tree-LSTM that propagates information first bottom-up then top-down, which allows each token to access information from the entire tree; and (2) a linguistically motivated head-first decoder that emphasizes the central role of the head and linearizes the subtree by incrementally attaching the dependents on both sides of the head.
Learning the Dyck Language with Attention-based Seq2Seq Models
The generalized Dyck language has been used to analyze the ability of Recurrent Neural Networks (RNNs) to learn context-free grammars (CFGs).
Who Sides with Whom? Towards Computational Construction of Discourse Networks for Political Debates
Understanding the structures of political debates (which actors make what claims) is essential for understanding democratic political decision making.
An Environment for Relational Annotation of Political Debates
This paper describes the MARDY corpus annotation environment developed for a collaboration between political science and computational linguistics.
The (Non-)Utility of Structural Features in BiLSTM-based Dependency Parsers
Classical non-neural dependency parsers put considerable effort on the design of feature functions.
IMS at the PolEval 2018: A Bulky Ensemble Depedency Parser meets 12 Simple Rules for Predicting Enhanced Dependencies in Polish
In this paper we show which components of the system were the most responsible for its final performance.
Approximate Dynamic Oracle for Dependency Parsing with Reinforcement Learning
We present a general approach with reinforcement learning (RL) to approximate dynamic oracles for transition systems where exact dynamic oracles are difficult to derive.
NLATool: an Application for Enhanced Deep Text Understanding
The application combines supporting text annotation and enriching the text with additional information from a number of sources directly within the application.
Bridging resolution: Task definition, corpus resources and rule-based experiments
Recent work on bridging resolution has so far been based on the corpus ISNotes (Markert et al. 2012), as this was the only corpus available with unrestricted bridging annotation.
Supervised Rhyme Detection with Siamese Recurrent Networks
We present the first supervised approach to rhyme detection with Siamese Recurrent Networks (SRN) that offer near perfect performance (97{\%} accuracy) with a single model on rhyme pairs for German, English and French, allowing future large scale analyses.
Polyglot Semantic Parsing in APIs
Traditional approaches to semantic parsing (SP) work by training individual models for each available parallel dataset of text-meaning pairs.
The Code2Text Challenge: Text Generation in Source Libraries
We propose a new shared task for tactical data-to-text generation in the domain of source code libraries.
Multi-modular domain-tailored OCR post-correction
One of the main obstacles for many Digital Humanities projects is the low data availability.
IMS at the CoNLL 2017 UD Shared Task: CRFs and Perceptrons Meet Neural Networks
This paper presents the IMS contribution to the CoNLL 2017 Shared Task.
The Code2Text Challenge: Text Generation in Source Code Libraries
We propose a new shared task for tactical data-to-text generation in the domain of source code libraries.
Function Assistant: A Tool for NL Querying of APIs
For a given text query and background API, the tool finds candidate functions by performing a translation from the text to known representations in the API using the semantic parsing approach of Richardson and Kuhn (2017).
Learning Semantic Correspondences in Technical Documentation
We consider the problem of translating high-level textual descriptions to formal representations in technical documentation as part of an effort to model the meaning of such documentation.
Flexible and Reliable Text Analytics in the Digital Humanities -- Some Methodological Considerations
I start this talk by sketching some sample scenarios of Digital Humanities projects which involve various Humanities and Social Science disciplines, noting that the potential for a meaningful contribution to higher-level questions is highest when the employed language technological models are carefully tailored both (a) to characteristics of the given target corpus, and (b) to relevant analytical subtasks feeding the discipline-specific research questions.
Named Entity Disambiguation for little known referents: a topic-based approach
We propose an approach to Named Entity Disambiguation that avoids a problem of standard work on the task (likewise affecting fully supervised, weakly supervised, or distantly supervised machine learning techniques): the treatment of name mentions referring to people with no (or very little) coverage in the textual training data is systematically incorrect.
IMS HotCoref DE: A Data-driven Co-reference Resolver for German
This paper presents a data-driven co-reference resolution system for German that has been adapted from IMS HotCoref, a co-reference resolver for English.
Learning from Within? Comparing PoS Tagging Approaches for Historical Text
In this paper, we investigate unsupervised and semi-supervised methods for part-of-speech (PoS) tagging in the context of historical German text.
Learning to Make Inferences in a Semantic Parsing Task
We introduce a new approach to training a semantic parser that uses textual entailment judgements as supervision.
A Corpus of Comparisons in Product Reviews
For each sentence we have annotated detailed information about the comparisons it contains: The comparative predicate that expresses the comparison, the type of the comparison, the two entities that are being compared, and the aspect they are compared in.
An Out-of-Domain Test Suite for Dependency Parsing of German
We present a dependency conversion of five German test sets from five different genres.
UnixMan Corpus: A Resource for Language Learning in the Unix Domain
We present a new resource, the UnixMan Corpus, for studying language learning it the domain of Unix utility manuals.
Converting an HPSG-based Treebank into its Parallel Dependency-based Treebank
In this paper, we introduce an algorithm to convert an HPSG-based treebank into its parallel dependency-based treebank.
Textual Emigration Analysis (TEA)
We present a web-based application which is called TEA (Textual Emigration Analysis) as a showcase that applies textual analysis for the humanities.
Exploring the utility of coreference chains for improved identification of personal names
In our experiments on real data we obtain comparable results.
A Corpus-based Study of the German Recipient Passive
In this paper, we investigate the usage of a non-canonical German passive alternation for ditransitive verbs, the recipient passive, in naturally occuring corpus data.
Making Ellipses Explicit in Dependency Conversion for a German Treebank
We present a carefully designed dependency conversion of the German phrase-structure treebank TiGer that explicitly represents verb ellipses by introducing empty nodes into the tree.
