Simulation data and pre-trained Graph Neural Network (GNN) models produced in 1. Silva, "Learning the dynamics of a one-dimensional plasma model with graph neural networks", arXiv:2310.17646 (2023) 2 J.
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FrameNet is a linguistic knowledge graph containing information about lexical and predicate argument semantics of the English language.
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PubMedCite is a domain-specific dataset with about 192K biomedical scientific papers and a large citation graph preserving 917K citation relationships between them.
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The CHILI-3K dataset is a medium-scale graph dataset (with overall >6M nodes, >49M edges) of mono-metallic oxide nanomaterials generated from 12 selected crystal types.
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…It was created by (a) generating questions with multiple answers from Wikipedia's knowledge graph and tables, (b) automatically pairing answers with supporting evidence in Wikipedia paragraphs, and (c)
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…Dialogues are distilled by contextualizing social commonsense knowledge from a knowledge graph (Atomic10x).
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…RoMQA contains clusters of questions that are derived from related constraints mined from the Wikidata knowledge graph.
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KGRC-RDF-star is an RDF-star dataset converted from KGRC-RDF, which is a Knowledge graph dataset of novel stories. KGRC-RDF-star is a complex RDF-star graph dataset that contains nested structures of statements and scenes, e.g., "Person A said "Person B saw "Person C was in D" " ."
…From paper: A context-aware citation recommendation model with BERT and graph convolutional networks
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This dataset is a Wikipedia dump, split by relations to perform Few-Shot Knowledge Graph Completion.
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…NeurIPS Dataset Track 2023 2 FedRule: Federated Rule Recommendation System with Graph Neural Networks. IoTDI 2023
…It has been built by manually examining the 2-hop link existing in the knowledge graph of TREx-1p, and select eight 2- hop relation types that make sense to humans
VANiLLa is a dataset for Question Answering over Knowledge Graphs (KGQA) offering answers in natural language sentences.
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JerichoWorld is a dataset that enables the creation of learning agents that can build knowledge graph-based world models of interactive narratives. JerichoWorld provides 24,198 mappings between rich natural language observations and: (1) knowledge graphs that reflect the world state in the form of a map; (2) natural language actions that are guaranteed
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…This website is meant to be browsed both by humans and machines alike, and can also be accessed via a convenient JSON API, or via the graph-tool library. The network datasets themselves are available in several machine-readable formats, in particular gt, GraphML, GML and CSV.
…A bipartite graph connecting entities and documents is first built and the answer for each query is located by traversal on this graph.
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VirtualHome2KG is a system for constructing and augmenting knowledge graphs (KGs) of daily living activities using virtual space. We also provide an ontology to describe the structure of the KGs.
The CHILI-100K dataset is a large-scale graph dataset (with overall >183M nodes, >1.2B edges) of nanomaterials generated from experimentally determined crystal structures.
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…Each AMR is a single rooted, directed graph. AMRs include PropBank semantic roles, within-sentence coreference, named entities and types, modality, negation, questions, quantities, and so on.
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This dataset comprises high-quality, targeted spear-phishing emails created using a proprietary system that harnesses the power of LLMs and knowledge graphs.
…We introduce the new task of multimodal analogical reasoning over knowledge graphs, which requires multimodal reasoning ability with the help of background knowledge.
…Traffic Accident Prediction (TAP) data repository offers extensive coverage for 1,000 US cities (TAP-city) and 49 states (TAP-state), providing real-world road structure data that can be easily used for graph-based machine learning methods such as Graph Neural Networks.
…The data is derived from the SoMeSci Knowledge Graph of software mentions. Subtask 1 deals with the recognition of software mentions and the classification of mention (e.g. Krüger, “SoMeSci—A 5 Star Open Data Gold Standard Knowledge Graph of Software Mentions in Scientific Articles,” in Proceedings of the 30th ACM International Conference on Information and Knowledge Management
…We construct a multi-relation graph based on the supplier, customer, shareholder, and financial information disclosed in the financial statements of Chinese companies.
…We here abstract the problem into a new benchmark for node classification in a geo-referenced graph. Solving it requires learning the spatial layout of the organ including symmetries.
InferWiki is a Knowledge Graph Completion (KGC) dataset that improves upon existing benchmarks in inferential ability, assumptions, and patterns.
ConvQuestions is the first realistic benchmark for conversational question answering over knowledge graphs. It contains 11,200 conversations which can be evaluated over Wikidata. For suitability to knowledge graphs, questions were constrained to be objective or factoid in nature, but no other restrictive guidelines were set.
…Given a text query and list of molecules without any reference textual information (represented, for example, as SMILES strings, graphs, or other equivalent representations) retrieve the molecule corresponding This requires the integration of two very different types of information: the structured knowledge represented by text and the chemical properties present in molecular graphs.
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TextWorld KG is a dynamic Knowledge Graph (KG) extraction dataset. It is based on a set of text-based games generated using.
…2021] to generate 2D molecular graphs. We also remove texts with less than 4 words, and crops descriptions with more than 256 words.
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In this work we create a question answering dataset over the DBLP scholarly knowledge graph (KG).
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…and test responses of children aged 9 through 12, as they participate in a robot-mediated human-human collaborative learning activity named JUSThink, where children in teams of two solve a problem on graphs
ParaQA is a question answering (QA) dataset with multiple paraphrased responses for single-turn conversation over knowledge graphs (KG).
…The floorplans are annotated with room outline polygons, doors/windows as line segments, object-icons as axis-aligned bounding boxes, room-door-room connectivity graphs, and photo-room assignments. Generated room-door-room connectivity graphs for floorplans. Annotated all windows, doors, and other wall openings, and associated them with corresponding rooms.
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FreebaseQA is a data set for open-domain QA over the Freebase knowledge graph.
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…identifying and collecting data on Wikipedia and expanding its analytical potential, after collecting different data from various sources and processing them, we have generated a dedicated Wikipedia Knowledge Graph We share this Knowledge Graph dataset in an open way, aiming to be useful for a wide range of researchers, such as informetricians, sociologists or data scientists.
…Most importantly we overcome the limitations of existing probing datasets by (1) having a larger variety of knowledge graph relations, (2) it contains single- and multi-token entities, (3) we use relations
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…With their familiar format, the explanations are geared towards commonsense reasoners operating on knowledge graphs and serve as a starting point for ongoing work on improving such systems.
…It contains multimodal data (visual data, temporal-graphs and audio) careful-selected from publicly available videos of dancers performing representative movements of the music style and audio data from
…TRIPOD is extended in Movie Summarization via Sparse Graph Construction with more movies in the test set (122 now in total) and multimodal features extracted from the full-length movie videos.
…Each sentence is paired with a graph that represents its whole-sentence meaning in a tree-structure.
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…The distinguishing characteristic of LargeST lies not only in its extensive graph size, encompassing a total of 8,600 sensors in California, but also in its substantial temporal coverage and rich node
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…Filtering images The first step is focused on filtering images that have meaningful scene graphs and captions. We filtered all the scene graphs that did not contain any edges. images pass this filter. The relationships should be verbs and not contain nouns or pronouns. We filter all scene graphs that contain an edge not tagged as a verb or that the tag is not in an ad-hoc list of allowed non-verb keywords.
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MuMiN is a misinformation graph dataset containing rich social media data (tweets, replies, users, images, articles, hashtags), spanning 21 million tweets belonging to 26 thousand Twitter threads, each
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Graph Neural Networks (GNNs) have gained traction across different domains such as transportation, bio-informatics, language processing, and computer vision.
…Given the lack of reliable ground truth data, we present SoMeSci - Software Mentions in Science - a gold standard knowledge graph of software mentions in scientific articles.
…We create the puzzles to encompass a diverse array of mathematical and algorithmic topics such as boolean logic, combinatorics, graph theory, optimization, search, etc., aiming to evaluate the gap between