| Challenge: | Existing systems for knowledge extraction from natural language sentences are lacking for all languages. |
| Approach: | They propose a Korean knowledge extraction system and web interface for enriching a KBox knowledge base based on the Korean DBpedia. |
| Outcome: | The proposed system can extract factual knowledge from natural language sentences . the endpoint can be used to add knowledge to a KBox knowledge base anytime and anywhere . |
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| Challenge: | Existing studies focus on the extraction itself and rely on Named Entity Disambiguation (NED) to map triples into knowledge base (KB) enrichment. |
| Approach: | They propose an end-to-end relation extraction model for knowledge base enrichment based on a neural encoder-decoder model . they propose to extract entities and their relationships from sentences in the form of triples and map the elements of the extracted triples to an existing KB in an end to end manner. |
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Knowledge Extraction From Texts Based on Wikidata (2022.naacl-industry)
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| Challenge: | Existing knowledge extraction pipelines for English are not suitable for enterprise use. |
| Approach: | They propose a knowledge extraction pipeline for English which can be further used for building an entreprise-specific knowledge base. |
| Outcome: | The proposed pipeline can be used to build an entreprise-specific knowledge base. |
Connecting Language and Knowledge with Heterogeneous Representations for Neural Relation Extraction (N19-1)
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| Challenge: | Knowledge Bases (KBs) require constant updating to reflect changes to the world they represent. |
| Approach: | They propose a framework that unifies learning of RE and KBE models . the framework is based on a relation extraction task that uses a KB relation to a phrase . |
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Simple and Effective Knowledge-Driven Query Expansion for QA-Based Product Attribute Extraction (2022.acl-short)
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| Challenge: | Existing approaches to extract value from product data for a large number of attributes are not effective for rare and ambiguous attributes. |
| Approach: | They propose to use attributes as knowledge to expand AVE queries by retrieving possible answers from training data. |
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Knowledge-Augmented Methods for Natural Language Processing (2022.acl-tutorials)
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| Challenge: | Knowledge in natural language processing (NLP) is a rising trend especially after the advent of large scale pre-trained models. |
| Approach: | This tutorial introduces the key steps in integrating knowledge into natural language processing (NLP) it introduces knowledge grounding from text, knowledge representation and fusing. |
| Outcome: | This tutorial introduces the key steps in integrating knowledge into natural language processing including knowledge grounding from text, knowledge representation and fusing. |
Knowledge Extraction on Semi-Structured Content: Does It Remain Relevant for Question Answering in the Era of LLMs? (2026.eacl-long)
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Kai Sun, Yin Huang, Srishti Mehra, Mohammad Kachuee, Xilun Chen, Renjie Tao, Zhaojiang Lin, Andrea Jessee, Nirav Shah, Alex L Betty, Yue Liu, Anuj Kumar, Wen-tau Yih, Xin Luna Dong
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KnowCoder: Coding Structured Knowledge into LLMs for Universal Information Extraction (2024.acl-long)
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Zixuan Li, Yutao Zeng, Yuxin Zuo, Weicheng Ren, Wenxuan Liu, Miao Su, Yucan Guo, Yantao Liu, Lixiang Lixiang, Zhilei Hu, Long Bai, Wei Li, Yidan Liu, Pan Yang, Xiaolong Jin, Jiafeng Guo, Xueqi Cheng
| Challenge: | None. None.. None! |
| Approach: | None. None.. None! |
| Outcome: | None. None. No. : |
X-WikiRE: A Large, Multilingual Resource for Relation Extraction as Machine Comprehension (D19-61)
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| Challenge: | Existing knowledge bases are heavily biased towards English, but Wikipedias cover very different topics in different languages. |
| Approach: | They propose a multilingual dataset that frams relation extraction as a machine reading problem. |
| Outcome: | The proposed model can be used to transfer models cross-lingually and improves knowledge base completion across languages. |
mOKB6: A Multilingual Open Knowledge Base Completion Benchmark (2023.acl-short)
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| Challenge: | Open knowledge bases (Open KBCs) are constructed from triples of the form, which can be denoted as (s, r, o) by using open information extraction (Open IE) systems. |
| Approach: | They construct a dataset with facts from Wikipedia in six languages . they use open information extraction systems to extract triples from text . |
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Rule-KBQA: Rule-Guided Reasoning for Complex Knowledge Base Question Answering with Large Language Models (2025.coling-main)
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| Challenge: | Existing methods for knowledge base question answering lack grammaticality, faithfulness, and controllability due to hallucinations in the reasoning process. |
| Approach: | They propose a framework that employs learned rules to guide the generation of logical forms. |
| Outcome: | The proposed method achieves competitive results on standard KBQA datasets. |