Papers with NEL
Scalable graph-based method for individual named entity identification (D19-53)
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| Challenge: | Named entity recognition (NED) is a method for identifying named entities within a knowledge base. |
| Approach: | They propose a method for individual identification requiring few annotated data samples. |
| Outcome: | The proposed method is well-motivated for integration in real systems. |
Entity Resolution in Open-domain Conversations (2021.naacl-industry)
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Mingyue Shang, Tong Wang, Mihail Eric, Jiangning Chen, Jiyang Wang, Matthew Welch, Tiantong Deng, Akshay Grewal, Han Wang, Yue Liu, Yang Liu, Dilek Hakkani-Tur
| Challenge: | Recent work on incorporating external knowledge into the response generation models has attracted great interest. |
| Approach: | They propose a neural entity linking approach to incorporate external knowledge into the response generation models to improve the relevancy of retrieved knowledge. |
| Outcome: | The proposed approach outperforms the baseline model by 62.8% relative to the baseline. |
AVEN-GR: Attribute Value Extraction and Normalization using product GRaphs (2023.acl-industry)
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| Challenge: | Query Attribute Understanding (QAU) is a sub-component of QU that involves extracting named attributes from user queries. |
| Approach: | They propose a novel end-to-end approach that solves Named Entity Recognition and Entity Linking for QAU . they propose utilizing product graphs to enhance the representation of query entities . |
| Outcome: | The proposed approach solves Named Entity Recognition and Entity Linking and enables open-world reasoning for QAU. |
Goodwill Hunting: Analyzing and Repurposing Off-the-Shelf Named Entity Linking Systems (2021.naacl-industry)
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| Challenge: | Named entity linking (NEL) is a preprocessing step in commercial systems . a small organization or individual could use an off-the-shelf system to accomplish the same objectives . |
| Approach: | They examine how to repurpose off-the-shelf NEL systems to correct sport-related errors. |
| Outcome: | The proposed model can improve sports question-answering accuracy by 25% . the proposed model is based on the best available model . |
Strong Heuristics for Named Entity Linking (2022.naacl-srw)
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| Challenge: | Named entity linking (NEL) is a challenging task due to the frequency of unseen and emerging entities, which necessitates the use of unsupervised or zero-shot methods. |
| Approach: | They propose to map speaker-attributed quotes to a unique identifier in a referent knowledge base and then use it to resolve the ambiguity. |
| Outcome: | The proposed method disambiguates 94% and 63% of the mentions on Quotebank and the AIDA-CoNLL benchmark, respectively. |
Improving Text-to-SQL Semantic Parsing with Fine-grained Query Understanding (2022.emnlp-industry)
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Jun Wang, Patrick Ng, Alexander Hanbo Li, Jiarong Jiang, Zhiguo Wang, Bing Xiang, Ramesh Nallapati, Sudipta Sengupta
| Challenge: | Recent research on Text-to-SQL semantic parsing relies on parser or heuristic based approach to understand natural language query. |
| Approach: | They propose a general-purpose, modular neural semantic parsing framework that is based on token-level fine-grained query understanding. |
| Outcome: | The proposed framework outperforms the state-of-the-art model by 2.7% on a WikiTableQuestions test set. |
Framing Named Entity Linking Error Types (L18-1)
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| Challenge: | Named Entity Linking (NEL) and relation extraction forms the backbone of Knowledge Base Population tasks. |
| Approach: | They propose a taxonomy to frame common errors and apply it to four well-known Named Entity Linking systems. |
| Outcome: | The proposed taxonomy was applied to four well-known Named Entity Linking systems on three gold standards. |
A Domain-Specific Curated Benchmark for Entity and Document-Level Relation Extraction (2026.findings-eacl)
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Marco Martinelli, Stefano Marchesin, Vanessa Bonato, Giorgio Di Nunzio, Nicola Ferro, Ornella Irrera, Laura Menotti, Federica Vezzani, Gianmaria Silvello
| Challenge: | Existing biomedical IE benchmarks are narrow in scope and rely heavily on distantly supervised annotations. |
| Approach: | They propose a benchmark for Information Extraction (IE) that annotates entities, concept-level links, and relations manually from PubMed abstracts. |
| Outcome: | The GutBrainIE benchmark is based on more than 1,600 PubMed abstracts, manually annotated by biomedical and terminological experts with fine-grained entities, concept-level links, and relations. |
The Bulgarian Event Corpus: Overview and Initial NER Experiments (2022.lrec-1)
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| Challenge: | Initial experiments on standard NER task due to complexity of dataset and rich NE annotation scheme are promising with respect to some labels and give insights on handling better other ones. |
| Approach: | They describe a Bulgarian Event Corpus (BEC) that includes named entities and events with their roles. |
| Outcome: | The proposed corpus is multi-domain and oriented towards Social Sciences and Humanities (SSH) it includes named entities and events with their roles. |
Learn to Not Link: Exploring NIL Prediction in Entity Linking (2023.findings-acl)
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| Challenge: | Entity linking models have been successful in capturing semantic features, but the NIL prediction problem has not been addressed. |
| Approach: | They propose an entity linking dataset that categorizes mentions linking to NIL into Missing Entity and Non-Entity Phrases. |
| Outcome: | The proposed dataset categorizes mentions linking to NIL into Missing Entity and Non-Entity Phrase categories and ensures the presence of mentions by human annotation and entity masking. |
SlugNERDS: A Named Entity Recognition Tool for Open Domain Dialogue Systems (L18-1)
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| Challenge: | UCSC researchers have developed an open domain social bot aimed at casual conversation . NER and NEL are important preprocessing steps for understanding user intent in open domain dialogue systems. |
| Approach: | They propose a tool for NER and NEL in open domain dialogue that addresses these challenges . they also propose two corpora based on 10,000 real user conversations . |
| Outcome: | The proposed open domain social bot is aimed at casual conversation. |