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Found 18 papers, 7 papers with code
Unleashing annotations with TextAnnotator: Multimedia, multi-perspective document views for ubiquitous annotation
We argue that mainly due to technical innovation in the landscape of annotation tools, a conceptual change in annotation models and processes is also on the horizon.
Tafsir Dataset: A Novel Multi-Task Benchmark for Named Entity Recognition and Topic Modeling in Classical Arabic Literature
Various historical languages, which used to be lingua franca of science and arts, deserve the attention of current NLP research.
Iconic Gesture Semantics
Informational evaluation is spelled out as extended exemplification (extemplification) in terms of perceptual classification of a gesture's visual iconic model.
Syntactic Language Change in English and German: Metrics, Parsers, and Convergences
Even though we have evidence that recent parsers trained on modern treebanks are not heavily affected by data 'noise' such as spelling changes and OCR errors in our historic data, we find that results of syntactic language change are sensitive to the parsers involved, which is a caution against using a single parser for evaluating syntactic language change as done in previous work.
German Parliamentary Corpus (GerParCor)
Parliamentary debates represent a large and partly unexploited treasure trove of publicly accessible texts.
I still have Time(s): Extending HeidelTime for German Texts
HeidelTime is one of the most widespread and successful tools for detecting temporal expressions in texts.
What do Toothbrushes do in the Kitchen? How Transformers Think our World is Structured
In this paper we utilize this research on biases to investigate to what extent transformer-based language models allow for extracting knowledge about object relations (X occurs in Y; X consists of Z; action A involves using X).
Multi-Type-TD-TSR -- Extracting Tables from Document Images using a Multi-stage Pipeline for Table Detection and Table Structure Recognition: from OCR to Structured Table Representations
It utilizes state-of-the-art deep learning models for table detection and differentiates between 3 different types of tables based on the tables' borders.
Optical Character Recognition
Optical Character Recognition (OCR)
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Multiple Texts as a Limiting Factor in Online Learning: Quantifying (Dis-)similarities of Knowledge Networks across Languages
From the perspective of educational science, the article develops a computational model of the information landscape from which multiple texts are drawn as typical input of web-based reading.
Computational linguistic assessment of textbook and online learning media by means of threshold concepts in business education
The two main findings can be summarized as follows: Firstly, the three kinds of resources can indeed be distinguished in terms of their threshold concepts' profiles.
The Frankfurt Latin Lexicon: From Morphological Expansion and Word Embeddings to SemioGraphs
In this article we present the Frankfurt Latin Lexicon (FLL), a lexical resource for Medieval Latin that is used both for the lemmatization of Latin texts and for the post-editing of lemmatizations.
From Topic Networks to Distributed Cognitive Maps: Zipfian Topic Universes in the Area of Volunteered Geographic Information
To this end, we explore Volunteered Geographic Information (VGI) to model texts addressing places at the level of cities or regions with the help of so-called topic networks.
When Specialization Helps: Using Pooled Contextualized Embeddings to Detect Chemical and Biomedical Entities in Spanish
The recognition of pharmacological substances, compounds and proteins is an essential preliminary work for the recognition of relations between chemicals and other biomedically relevant units.
SenseFitting: Sense Level Semantic Specialization of Word Embeddings for Word Sense Disambiguation
We outperform knowledge-based WSD methods by up to 25% F1-score and produce a new state-of-the-art on the German sense-annotated dataset WebCAGe.
Resource-Size matters: Improving Neural Named Entity Recognition with Optimized Large Corpora
This study improves the performance of neural named entity recognition by a margin of up to 11% in F-score on the example of a low-resource language like German, thereby outperforming existing baselines and establishing a new state-of-the-art on each single open-source dataset.
On the Linearity of Semantic Change: Investigating Meaning Variation via Dynamic Graph Models
We consider two graph models of semantic change.
Language classification from bilingual word embedding graphs
We study the role of the second language in bilingual word embeddings in monolingual semantic evaluation tasks.
Complex Decomposition of the Negative Distance kernel
Our evaluation shows that the power kernel produces F-scores that are comparable to the reference kernels, but is -- except for the linear kernel -- faster to compute.
