mlsanityData to 7 Oct 2026

KnowGL: Knowledge Generation and Linking from Text

arXiv 2210.13952 ↗First posted 25 Oct 2022cs.CL cs.AI cs.IRcited by 13

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Abstract (arXiv)

We propose KnowGL, a tool that allows converting text into structured relational data represented as a set of ABox assertions compliant with the TBox of a given Knowledge Graph (KG), such as Wikidata. We address this problem as a sequence generation task by leveraging pre-trained sequence-to-sequence language models, e.g. BART. Given a sentence, we fine-tune such models to detect pairs of entity mentions and jointly generate a set of facts consisting of the full set of semantic annotations for a KG, such as entity labels, entity types, and their relationships. To showcase the capabilities of our tool, we build a web application consisting of a set of UI widgets that help users to navigate through the semantic data extracted from a given input text. We make the KnowGL model available at https://huggingface.co/ibm/knowgl-large.

Key facts. Cited by 13 papers in the map (data through 7 Oct 2026). Builds on 17 of its 25 references that are in the map. First posted on arXiv 25 Oct 2022.

Builds on

17 of 25 references.

References · 17

  1. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,491
  2. 2019BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehensioncited by 5,874
  3. 2020Knowledge Graphscited by 619
  4. 2020Autoregressive Entity Retrievalcited by 333
  5. 2022Re2G: Retrieve, Rerank, Generatecited by 102
  6. 2019Scalable Zero-shot Entity Linking with Dense Entity Retrievalcited by 85
  7. 2021Improving Named Entity Recognition by External Context Retrieving and Cooperative Learningcited by 76
  8. 2020Don't Parse, Generate! A Sequence to Sequence Architecture for Task-Oriented Semantic Parsingcited by 59
  9. 2021GenIE: Generative Information Extractioncited by 53
  10. 2021Text-to-Table: A New Way of Information Extractioncited by 47
  11. 2021Word-Level Coreference Resolutioncited by 40
  12. 2021Structure-aware Fine-tuning of Sequence-to-sequence Transformers for Transition-based AMR Parsingcited by 25
5 more
  1. 2021Robust Retrieval Augmented Generation for Zero-shot Slot Fillingcited by 24
  2. 2021ReGen: Reinforcement Learning for Text and Knowledge Base Generation using Pretrained Language Modelscited by 16
  3. 2021Generative Relation Linking for Question Answering over Knowledge Basescited by 14
  4. 2022A Generative Model for Relation Extraction and Classificationcited by 5
  5. 2022Knowledge Graph Induction enabling Recommending and Trend Analysis: A Corporate Research Community Use Casecited by 2

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 3; 2024: 2; 2025: 5; 2026: 3.

13 papers.

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  1. 2023Struc-Bench: Are Large Language Models Really Good at Generating Complex Structured Data?cited by 16
  2. 2024ReLiK: Retrieve and LinK, Fast and Accurate Entity Linking and Relation Extraction on an Academic Budgetcited by 16
  3. 2023WebIE: Faithful and Robust Information Extraction on the Webcited by 8
  4. 2023Knowledge Base Completion for Long-Tail Entitiescited by 7
  5. 2024DocTabQA: Answering Questions from Long Documents Using Tablescited by 6
  6. 2025Automatic Prompt Optimization for Knowledge Graph Construction: Insights from an Empirical Studycited by 6
  7. 2025Transduction is All You Need for Structured Data Workflowscited by 3
  8. 2026Clinical Knowledge Graph Construction and Evaluation with Multi-LLMs via Retrieval-Augmented Generationcited by 2
  9. 2025A systematic review of relation extraction task since the emergence of Transformerscited by 1
  10. 2026GRID: Graph Representation of Intelligence Data for Security Text Knowledge Graph Constructioncited by 1
  11. 2025EMERGE: A Benchmark for Updating Knowledge Graphs with Emerging Textual Knowledgecited by 0
  12. 2025Kastor: Fine-tuned Small Language Models for Shape-based Active Relation Extractioncited by 0
1 more
  1. 2026Text Data Integrationcited by 0