WikiGraphs is a dataset of Wikipedia articles each paired with a knowledge graph, to facilitate the research in conditional text generation, graph generation and graph representation learning. Existing graph-text paired datasets typically contain small graphs and short text (1 or few sentences), thus limiting the capabilities of the models that can be learned on the data. WikiGraphs is collected by pairing each Wikipedia article from the established WikiText-103 benchmark with a subgraph from the Freebase knowledge graph. Both the graphs and the text data are of significantly larger scale compared to prior graph-text paired datasets.

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The dataset contains constructed multi-modal features (visual and textual), pseudo-labels (on heritage values and attributes), and graph structures (with temporal, social, and spatial links) constructed

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SciGraphQA is a large-scale, open-domain dataset focused on generating multi-turn conversational question-answering dialogues centered around understanding and describing scientific graphs and figures. Each sample in ScFiGraphQA consists of a scientific graph image sourced from papers on ArXiv, accompanied by rich textual context including the paper's title, abstract, figure caption, and a paragraph The key motivation behind SciGraphQA is providing a large-scale resource to support research and development of multi-modal AI systems that can engage in informative, open-ended conversations about graphs Potential use cases of SciGraphQA include pre-training and benchmarking multi-modal conversational models for scientific graph comprehension, building AI assistants that can discuss data insights, and The academic source material also provides a way to evaluate model capabilities on expert-level graphs spanning diverse topics and complex visual encodings.

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The Microsoft Academic Graph is a heterogeneous graph containing scientific publication records, citation relationships between those publications, as well as authors, institutions, journals, conferences

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Worldtree is a corpus of explanation graphs, explanatory role ratings, and associated tablestore. It contains explanation graphs for 1,680 questions, and 4,950 tablestore rows across 62 semi-structured tables are provided. This data is intended to be paired with the AI2 Mercury Licensed questions.

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…EHR data are typically stored in a relational database, which can also be converted to a directed acyclic graph, allowing two approaches for EHR QA: Table-based QA and Knowledge Graph-based QA. MIMIC-SPARQL dataset provides graph-based EHR QA data where natural language queries are converted to SPARQL instead of SQL

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PDDL dataset of Rearrangement tasks in large-scale 3D scene graphs.

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Multi-Modal Hate Speech Detection with Graph Context. 18k+ labels, 8k+ discussions, 900k+ comments.

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The datasets of "Time Interval-enhanced Graph Neural Network for Shared-account Cross-domain Sequential Recommendation" (TNNLs 2022)

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The datasets of "Towards Lightweight Cross-domain Sequential Recommendation via External Attention-enhanced Graph Convolution Network" (DASFAA 2023)

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…The dataset has been integrated with Pytorch Geometric (PyG) and Deep Graph Library (DGL). You can load the dataset after installing the latest versions of PyG or DGL. The UPFD dataset includes two sets of tree-structured graphs curated for evaluating binary graph classification, graph anomaly detection, and fake/real news detection tasks. The news retweet graphs were originally extracted by FakeNewsNet. Each graph is a hierarchical tree-structured graph where the root node represents the news; the leaf nodes are Twitter users who retweeted the root news. The dataset statistics is shown below: | Data | #Graphs | #Fake News| #Total Nodes | #Total Edges | #Avg.

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VerbCL is a dataset that consists of the citation graph of court opinions, which cite previously published court opinions in support of their arguments. VerbCL is derived from CourtListener and introduces the task of highlight extraction as a single-document summarization task based on the citation graph.

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This is a Twitter dataset of 100,386 users along with up to 200 tweets from their timelines with a random-walk-based crawler on the retweet graph, with a subsample of 4,972 which is manually annotated The dataset can be used to examine the difference between user activity patterns, the content disseminated between hateful and normal users, and network centrality measurements in the sampled graph.

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Comet is a dataset which contains 11.5k user-assistant dialogs (totalling 103k utterances), grounded in simulated personal memory graphs.

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…It is used to generate flow graphs from procedural texts.

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NLPContributionGraph was introduced as Task 11 at SemEval 2021 for the first time. The task is defined on a dataset of Natural Language Processing (NLP) scholarly articles with their contributions structured to be integrable within Knowledge Graph infrastructures such as the Open Research Knowledge Graph.

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…The entire dataset constitutes a large connected citation graph.

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An RDF knowledge graph that provides comprehensive, current information about almost 400,000 machine learning publications. As a knowledge graph in the Linked Open Data cloud, we offer LPWC in multiple formats, from RDF dump files to a SPARQL endpoint for direct web queries, as well as a data source with resolvable URIs and Additionally, we supply knowledge graph embeddings, enabling LPWC to be readily applied in machine learning applications.

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DiaKG is a high-quality Chinese dataset for Diabetes knowledge graph. Based on this dataset, doctors, researchers, and enterprise developers can develop knowledge bases for clinical diagnosis, knowledge graphs, and auxiliary diagnostics to further explore the mysteries of

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Paper Field is built from the Microsoft Academic Graph and maps paper titles to one of 7 fields of study.

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…It consists of entities and passages from 10M Wikipedia articles linked to the Wikidata knowledge graph with 41K types.

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ScienceExamCER is a collection of resources for studying explanation-centered inference, including explanation graphs for 1,680 questions, with 4,950 tablestore rows, and other analyses of the knowledge

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…The images are synthetic, scientific-style figures from five classes: line plots, dot-line plots, vertical and horizontal bar graphs, and pie charts.

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…Knowledge graphs (KG) provide a visual representation in a graph that can reason and interpret from the underlying data, making them suitable for use in education and interactive learning. Creating knowledge graphs from unstructured text is challenging without an ontology or annotated dataset. However, data annotation for cybersecurity needs domain experts. This dataset can be used to construct knowledge graphs to teach cybersecurity and promote cognitive learning.

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…The logical forms show diversified graph structure of free schema, which poses great challenges on the model's ability to understand the semantics.

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This dataset includes reviews (ratings, text, helpfulness votes), product metadata (descriptions, category information, price, brand, and image features), and links (also viewed/also bought graphs).

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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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…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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…RoMQA contains clusters of questions that are derived from related constraints mined from the Wikidata knowledge graph.

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…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

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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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…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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ConceptNet is a knowledge graph that connects words and phrases of natural language with labeled edges.

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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.

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…The original files are originally split into train/test split, while other research efforts (https://github.com/2003pro/Graph2Tree) perform the train/dev/test split.

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…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

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…code tokens, ASTs, graphs), and several properties (e.g., metrics, static analysis results) for 50,000 Java projects from the 50KC dataset, with over 1.2 million classes and over 8 million methods.

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…By providing it open source (see License), we aim to motivate, support, and increase the application of database and knowledge graphs principles and techniques to the study of computational aspects of

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InferWiki is a Knowledge Graph Completion (KGC) dataset that improves upon existing benchmarks in inferential ability, assumptions, and patterns.

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KdConv is a Chinese multi-domain Knowledge-driven Conversation dataset, grounding the topics in multi-turn conversations to knowledge graphs.

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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.

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…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.

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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

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ParaQA is a question answering (QA) dataset with multiple paraphrased responses for single-turn conversation over knowledge graphs (KG).

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