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📢 #highlycited paper 📚 #CourseKG: An Educational #KnowledgeGraph Based on Course Information for #PrecisionTeaching 🔗 mdpi.com/2076-3417/14/7/2710 👨‍🔬 by Ying Li et al. 🏫 Beihang University/Beijing University of Technology #conceptionrecognition #relationextraction
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🔥 Read our Highly Cited Paper 📚 CourseKG: An Educational #KnowledgeGraph Based on Course Information for #PrecisionTeaching 🔗 mdpi.com/2076-3417/14/7/2710 👨‍🔬 Ying Li et al. 🏫 @Beihang1952 / @BJUT1960 #conceptionrecognition #relationextraction #smarteducation
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👉Are you on 🔥 for #knowledgegraphs #embeddings #entitymatching #relationextraction? Look at this exciting 18 months 🎓PostDoc🎓opportunity and send in your application! uni-mannheim.de/dws/career/h… Please RT!
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Great news our article "12 Shades of RDF" was accepted at the LMforKE Special Track at @eswc_conf ... And we just submitted the Camera Ready :) Let's discuss it at the end of May! #LLM #KG #RelationExtraction #StructuredExtraction
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LLMs for Information Extraction (Survey) ✅ Information Extraction (IE) focuses on extracting structural knowledge, such as entities, relations, and events, from natural language texts. ✅ This survey paper explores the recent trend of utilizing generative Large Language Models (LLMs) for information extraction (IE) tasks. ✅ The paper delves into this area by presenting: 1️⃣ Categorization: An extensive overview of existing works classified by IE subtasks and learning paradigms used. 2️⃣ Empirical analysis: Evaluation of the most advanced LLM-based methods for IE. 3️⃣ Trend identification: Discovery of emerging trends in applying LLMs for IE tasks. To summarize, this paper highlights the growing influence of LLMs in the field of IE and provides valuable insights and directions for future research. ☑️ Survey paper: arxiv.org/pdf/2312.17617.pdf #generativeai #llms #nlproc #nlp #deeplearning #informationextraction #ner #relationextraction
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If you are in #Tokyo tomorrow you might be interested in this talk I will give @chokkanorg #OkazakiLab on a #UnifiedVision of #WSD, #EntityLinking and #RelationExtraction! #NLProc nlp.c.titech.ac.jp/news/2023…

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I am delighted to present that our ARElight-0.24.0 system paper 🎊 has been accepted 🎊 at ECIR-2024! 🎆 dropbox.com/scl/fi/r3fjtargg… #arelight #ecir2024 #ecir #nlp #demonstation #demo #languagemodels #sentimentanalysis #pipeline #processing #relationextraction
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#LLMs can be used for #relationextraction as part of #AKGC. However, what issues exist for successful #fewshot training? Find out tomorrow at #nlp4kgc workshop - September 21, 11:30am. @lyndonjbnixon @moduluniversity @modultechnology #semanticsconf
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10 Jul 2023
We are presenting 6 research papers on a variety of #NLProc topics (#LLMs, #summarization, #RelationExtraction, #SemanticParsing and alignment) at #ACL2023! Don't miss them! babelscape.com/research#pubs #ACL2023NLP #NLU
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mREBEL and more: very proud of the results of this collaborative work between @Babelscape, @SapienzaNLP and @DiceResearch (@NgongaAxel) on #Multilingual #RelationExtraction in the @knowgraphs project! With @PereLluisHC @SimoneTedeschi_ @NgongaAxel
20 Jun 2023
📢Check out our new #ACL2023 paper! "REDFM: a Multilingual and Filtered Relation Extraction Dataset" 📄arxiv.org/abs/2306.09802 @PereLluisHC @SimoneTedeschi_ @NgongaAxel and @RNavigli #ACL2023NLP #NLProc #RelationExtraction #MultilingualNLP @knowgraphs 🧵1/7
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20 Jun 2023
🚀In our work we close the gap between languages for #RelationExtraction. We present an array of datasets and models to advance the current state of #multilingual Relation Extraction. 🧵2/7
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20 Jun 2023
📢Check out our new #ACL2023 paper! "REDFM: a Multilingual and Filtered Relation Extraction Dataset" 📄arxiv.org/abs/2306.09802 @PereLluisHC @SimoneTedeschi_ @NgongaAxel and @RNavigli #ACL2023NLP #NLProc #RelationExtraction #MultilingualNLP @knowgraphs 🧵1/7
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Congrats @monika_jain19!! In collaboration with @OyeKuldeep, happy to have one of our works on Neuro-Symbolic AI out. #nesyai #ontology #relationextraction #ecmlpkdd23 @iiitdcai @IIITDelhi @cseiiitd @ECMLPKDD
📢 Exciting News! Our research paper, "ReOnto: A Neuro-Symbolic Approach for Biomedical Relation Extraction", has been accepted at ECML PKDD '23. We propose a novel method that uses neuro-symbolic knowledge (ontologies graph neural nets) to predict relations. #nesyAI #ontology
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Good luck to @engr_manzoor in presenting the paper "RELD: A Knowledge Graph of Relation Extraction Datasets" at #ESWC2023!🚀👏 You can take a look at the paper here➡️ link.springer.com/chapter/10… #RelationExtraction #DICEontour #DICEreadme
I am filled with anticipation as I prepare to deliver our paper, titled "RELD: A Knowledge Graph of Relation Extraction Datasets," at #ESWC2023 today. Paper: link.springer.com/chapter/10… (Complete slides will follow after the #eswc_conf talk) @DiceResearch #Relation_extraction
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Which session are you following next? 👀 💡Lots of interesting papers in #KnowledgeGraphConstruction, #Reasoning, #Alignment, #Linking & #RelationExtraction in the Research, Resource and In-Use papers presented today in #ESWC2023
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Jennifer D’Souza and I gave a talk on The State of the Art Transformer Language Models for #KnowledgeGraph Construction from Text at the Knowledge Graph Conference 2023 knowledgegraph.tech/speakers… It was great to be part of KGC2023! @KGConference #KG #RelationExtraction
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