惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

阮一峰的网络日志
阮一峰的网络日志
博客园 - 司徒正美
D
DataBreaches.Net
宝玉的分享
宝玉的分享
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
博客园 - 【当耐特】
人人都是产品经理
人人都是产品经理
博客园 - Franky
让小产品的独立变现更简单 - ezindie.com
让小产品的独立变现更简单 - ezindie.com
IT之家
IT之家
博客园 - 三生石上(FineUI控件)
J
Java Code Geeks
腾讯CDC
博客园_首页
The Cloudflare Blog
S
SegmentFault 最新的问题
C
Check Point Blog
美团技术团队
爱范儿
爱范儿
大猫的无限游戏
大猫的无限游戏
Hugging Face - Blog
Hugging Face - Blog
T
The Blog of Author Tim Ferriss
A
About on SuperTechFans
Blog — PlanetScale
Blog — PlanetScale

Paper Index on ACL Anthology

A Bounded Coordination-Support Capability for Multi-Party Settings: Task-State Monitoring in Firefighter Incident Command A Dataset of Latin Etymologies Extracted from Wiktionary An Efficient Approach for Answering Not Readily Attainable Questions for RAG-based Applications Automated German Alt Text Generation for News Charts Call Support Copilot: A Reproducible Multimodal System for Speech Emotion Recognition, Intent Understanding, and Agent Assistance Can Large Language Models Replace Statistical Software? Code-Switching Detection in Multilingual Child Speech with SwissBERT Concept Extraction and Webb’s Depth of Knowledge: Comparing LLM Question Generation Pipelines for Educational Assessment Data Augmentation for Historical NER: A Systematic Comparison of Lexical and LLM-based Approaches Enhancing Retrieval via Cognitively Motivated Document Expansion Extending the Contact Hypothesis: Cross-Linguistic Evaluation of Religion and Nationality Bias When Prompting LLMs in German and Icelandic Extracting Article-Level Legal Dependencies from Swiss Federal Law using LLMs How Good is AI on Swiss Voting Booklets? A Multilingual OCR and Alignment Benchmark Optimizing Large Language Models for Robust Domain-Specific Text-to-SQL: From Prompting to Preference Alignment Proceedings of the 11th Edition of the Swiss Text Analytics Conference Reinforcement Learning for Latent-Space Thinking in LLMs RUMLEM: A Dictionary-Based Lemmatizer for Romansh Skill Extraction from Resumes and Job Offers across Six Languages Text vs. Phoneme Intermediates for Low-Resource Swiss German The Same Email, Signed Differently: Testing Negotiation Bias and Recommendation Stability in LLMs Which Skills Debate Reaches the Public? Comparing Scientific Literature and Media Coverage of AI and LLM Skill Impacts (2022–2025) Controlling Language and Style of Multi-lingual Generative Language Models with Control Vectors Hybrid Human-LLM Corpus Construction and LLM Evaluation for the Caused-Motion Construction Implicit and Indirect: Detecting Face-threatening and Paired Actions in Asynchronous Online Conversations Northern European Journal of Language Technology, Volume 11 A modular architecture for creating multimodal embodied agents with an episodic Knowledge Graph as an explainable and controllable long-term memory A Neural Approach to Discourse Relation Signal Detection An Analysis of Japanese Sentence-final Particle Yone: Compare Yone and Ne in Response Attribution and the discourse structure of reports Automatic Detection of the Bulgarian Evidential Renarrative
German Modal Particles as Discourse Signals
2026-04-20 · via Paper Index on ACL Anthology
Abstract

This study investigates the interaction of German modal particles like ja and doch with discourse structure. We conduct an acceptability study of modal particles in four discourse relations (CIRCUMSTANCE, CONDITION, EVIDENCE, JUSTIFY) to test predictions of (in)compatibilities derived from a corpus study by Döring and Repp (2019). As ratings for sentences representing the discourse relations CIRCUMSTANCE and CONDITION were significantly lower than for the two causal relations if presented with a modal particle, we confirm that modal particles and discourse structure interact. In a forced-choice study testing the particle ja’s effect on relation disambiguation, we show that ja supports a causal interpretation of an ambiguous context in the absence of explicit discourse markers. Our findings contribute to delineating the role of German modal particles in discourse, as we show that there is an interaction between discourse relations and modal particles, meaning that readers do not accept all modal particles in every discourse relation, and at least the modal particle ja serves as a non-connective discourse signal for causal relations.