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1 to 10 of 121 Results
Apr 24, 2024 - AIPHES
Mihaylov, Todor, 2024, "Knowledge-Enhanced Neural Networks for Machine Reading Comprehension [Source Code and Additional Material]", https://doi.org/10.11588/data/HU3ARF, heiDATA, V1
Machine Reading Comprehension is a language understanding task where a system is expected to read a given passage of text and typically answer questions about it. When humans assess the task of reading comprehension, in addition to the presented text, they usually use the knowled...
Feb 26, 2024 - RATIO_EXPLAIN
Becker, Maria, 2024, "CoCo-Ex", https://doi.org/10.11588/data/K8MCIW, heiDATA, V1
CoCo-Ex extracts meaningful concepts from natural language texts and maps them to conjunct concept nodes in ConceptNet, utilizing the maximum of relational information stored in the ConceptNet knowledge graph.
Feb 26, 2024 - RATIO_EXPLAIN
Becker, Maria, 2024, "LLMs4Implicit-Knowledge-Generation Public", https://doi.org/10.11588/data/5VTJ26, heiDATA, V1
Code for equipping pretrained language models (BART, GPT-2, XLNet) with commonsense knowledge for generating implicit knowledge statements between two sentences, by (i) finetuning the models on corpora enriched with implicit information; and by (ii) constraining models with key c...
Feb 26, 2024 - RATIO_EXPLAIN
Becker, Maria, 2024, "CO-NNECT", https://doi.org/10.11588/data/SAJAD3, heiDATA, V1
This repository contains our path generation framework Co-NNECT, in which we combine two models for establishing knowledge relations and paths between concepts from sentences, as a form of explicitation of implicit knowledge: COREC-LM (COmmonsense knowledge RElation Classificatio...
Feb 26, 2024 - RATIO_EXPLAIN
Becker, Maria, 2024, "IKAT-DE", https://doi.org/10.11588/data/4BA5LY, heiDATA, V1
A corpus consisting of high-quality human annotations of missing and implied information in argumentative texts (German version). The data is further annotated with semantic clause types and commonsense knowledge relations.
RATIO_EXPLAIN(Heidelberg University, Department of Computational Linguistics)
Feb 26, 2024
Open Research Data from the ExpLAIN project, a joint research project of the NLP Group at the Computational Linguistics Department of Heidelberg University and the Data and Web Science Groupat University of Mannheim.
Feb 26, 2024 - RATIO_EXPLAIN
Becker, Maria, 2024, "IKAT-EN", https://doi.org/10.11588/data/RUBM2E, heiDATA, V1, UNF:6:To3aHa8xO8P28fzpCz1Qvw== [fileUNF]
A corpus consisting of high-quality human annotations of missing and implied information in argumentative texts (English version). The data is further annotated with semantic clause types and commonsense knowledge relations.
Jan 17, 2024 - Natural Language Processing Group
Opitz, Juri Alexander, 2024, "Source code and data for the PhD Thesis "Metrics of Graph-Based Meaning Representations with Applications from Parsing Evaluation to Explainable NLG Evaluation and Semantic Search"", https://doi.org/10.11588/data/RAS7U7, heiDATA, V1
This dataset contains source code and data used in the PhD thesis "Metrics of Graph-Based Meaning Representations with Applications from Parsing Evaluation to Explainable NLG Evaluation and Semantic Search". The dataset is split into five repositories: S3BERT: Source code to run...
Natural Language Processing Group(Universität Heidelberg)
Jan 17, 2024
The main purpose of language is to encode and communicate information of all sorts. Our research focuses on semantics — the study of meaning — and how a machine can assign meaning to utterances: words, sentences and texts, as humans can do. Our work is linguistically informed and...
Nov 13, 2023 - Neural Techniques for German Dependency Parsing
Fankhauser, Peter; Do, Bich-Ngoc; Kupietz, Marc, 2023, "Neural Dependency Parser with Biaffine Attention", https://doi.org/10.11588/data/DZ9MUS, heiDATA, V1
This resource contains the code of the dependency parser used in the paper: Fankhauser, et al. (2020). "Evaluating a Dependency Parser on DeReKo". The parser is a re-implementation of the neural dependency parser from Dozat and Manning (2017). In addition, we include two pre-trai...
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