mlsanityData to 7 Oct 2026

BLINK with Elasticsearch for Efficient Entity Linking in Business Conversations

arXiv 2205.04438 ↗First posted 9 May 2022cs.CL cs.IR cs.LGcited by 13

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Abstract (arXiv)

An Entity Linking system aligns the textual mentions of entities in a text to their corresponding entries in a knowledge base. However, deploying a neural entity linking system for efficient real-time inference in production environments is a challenging task. In this work, we present a neural entity linking system that connects the product and organization type entities in business conversations to their corresponding Wikipedia and Wikidata entries. The proposed system leverages Elasticsearch to ensure inference efficiency when deployed in a resource limited cloud machine, and obtains significant improvements in terms of inference speed and memory consumption while retaining high accuracy.

Key facts. Cited by 13 papers in the map (data through 7 Oct 2026). Builds on 18 of its 31 references that are in the map. First posted on arXiv 9 May 2022.

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18 of 31 references.

References · 18

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  11. 2019Fine-Grained Entity Typing for Domain Independent Entity Linkingcited by 36
  12. 2021RockNER: A Simple Method to Create Adversarial Examples for Evaluating the Robustness of Named Entity Recognition Modelscited by 28
6 more
  1. 2020WSL-DS: Weakly Supervised Learning with Distant Supervision for Query Focused Multi-Document Abstractive Summarizationcited by 23
  2. 2019Falcon 2.0: An Entity and Relation Linking Tool over Wikidatacited by 21
  3. 2021Domain Adaptation with Pre-trained Transformers for Query Focused Abstractive Text Summarizationcited by 21
  4. 2020Interpretable Entity Representations through Large-Scale Typingcited by 19
  5. 2021CHOLAN: A Modular Approach for Neural Entity Linking on Wikipedia and Wikidatacited by 14
  6. 2021Survey on English Entity Linking on Wikidatacited by 6

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Citing papers per year: 2022: 4; 2023: 9.

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  1. 2023A Systematic Study and Comprehensive Evaluation of ChatGPT on Benchmark Datasetscited by 123
  2. 2023A Comprehensive Evaluation of Large Language Models on Benchmark Biomedical Text Processing Taskscited by 36
  3. 2023Building Real-World Meeting Summarization Systems using Large Language Models: A Practical Perspectivecited by 34
  4. 2023ChartSumm: A Comprehensive Benchmark for Automatic Chart Summarization of Long and Short Summariescited by 30
  5. 2023Are Large Language Models Reliable Judges? A Study on the Factuality Evaluation Capabilities of LLMscited by 23
  6. 2023Evaluation of ChatGPT on Biomedical Tasks: A Zero-Shot Comparison with Fine-Tuned Generative Transformerscited by 22
  7. 2023AI Coach Assist: An Automated Approach for Call Recommendation in Contact Centers for Agent Coachingcited by 8
  8. 2022An Effective, Performant Named Entity Recognition System for Noisy Business Telephone Conversation Transcriptscited by 7
  9. 2022Improving Named Entity Recognition in Telephone Conversations via Effective Active Learning with Human in the Loopcited by 7
  10. 2023CQSumDP: A ChatGPT-Annotated Resource for Query-Focused Abstractive Summarization Based on Debatepediacited by 7
  11. 2022Personal Entity, Concept, and Named Entity Linking in Conversationscited by 4
  12. 2022Entity-level Sentiment Analysis in Contact Center Telephone Conversationscited by 4
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  1. 2023CoRE-CoG: Conversational Recommendation of Entities using Constrained Generationcited by 0