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Extending a CRF-based named entity recognition model for Turkish well formed text and user generated content1

Gökhan Akın Şeker, Gülşen Eryiğit, Andreas Hotho, Robert Jäschke, Kristina Lerman, Andreas Hotho, Robert Jäschke, Kristina Lerman
2017 Semantic Web Journal  
This article presents the enhancements made to a Turkish named entity recognition model [5] (based on conditional random fields (CRFs) and originally tailored for well formed texts) in order to extend  ...  its covered named entity types, and also to process extra challenging user generated content coming with Web 2.0.  ...  Acknowledgements We would like to acknowledge that this work is part of a research project entitled "Parsing Web 2.0 Sentences" subsidized by the TUBITAK (Turkish Scienti fic and Technological Research  ... 
doi:10.3233/sw-170253 fatcat:6e47nqhzyjabrhl6t7cgijm7xm

Mining social semantics on the social web

Andreas Hotho, Robert Jäschke, Kristina Lerman, Andreas Hotho, Robert Jäschke, Kristina Lerman
2017 Semantic Web Journal  
-Extending a CRF-based Named Entity Recognition Model for Turkish Well Formed Text and User Generated Content by GökhanŞeker and Gülşen Eryigit: The detection of named entities is still a major challenge  ...  For example, content from the social web could be enriched and linked to the semantic web using named entity recognition and linking, as well as sentiment analysis.  ... 
doi:10.3233/sw-170272 fatcat:tn4i46l43faixbxa6q7zkpa3la

An evaluation of recent neural sequence tagging models in Turkish named entity recognition

Gizem Aras, Didem Makaroğlu, Seniz Demir, Altan Cakir
2021 Expert systems with applications  
Named entity recognition (NER) is an extensively studied task that extracts and classifies named entities in a text.  ...  Recent research efforts on Turkish, a less studied language with morphologically rich nature, have demonstrated the effectiveness of neural architectures on well-formed texts and yielded state-of-the art  ...  Acknowledgement Authors would like to thank Kemal Oflazer, Onur Güngör and Tunga Güngör for their assistance in obtaining the Turkish NER dataset.  ... 
doi:10.1016/j.eswa.2021.115049 fatcat:mpachywctzbhtkuwkwy7hovt5y

An Evaluation of Recent Neural Sequence Tagging Models in Turkish Named Entity Recognition [article]

Gizem Aras, Didem Makaroglu, Seniz Demir, Altan Cakir
2020 arXiv   pre-print
Named entity recognition (NER) is an extensively studied task that extracts and classifies named entities in a text.  ...  Recent research efforts on Turkish, a less studied language with morphologically rich nature, have demonstrated the effectiveness of neural architectures on well-formed texts and yielded state-of-the art  ...  Recently, neural models have been introduced to named entity task in well-formed and noisy texts (Al-Nabki et al., 2020) .  ... 
arXiv:2005.07692v2 fatcat:ongxceoqijbu7g4xjkb545dapm

Named Entity Recognition on Twitter for Turkish using Semi-supervised Learning with Word Embeddings [article]

Eda Okur and Hakan Demir and Arzucan Özgür
2018 arXiv   pre-print
In this study, we focused on the Named Entity Recognition (NER) problem on informal text types for Turkish. We utilized a semi-supervised learning approach based on neural networks.  ...  We made use of these obtained word embeddings, together with language independent features that are engineered to work better on informal text types, for generating a Turkish NER system on microblog texts  ...  We would also like to thank The Scientific and Technological Research Council of Turkey (TÜBİTAK), The Science Fellowships and Grant Programmes Department (BİDEB) for providing financial support with 2210  ... 
arXiv:1810.08732v1 fatcat:c5hvilxj7zaejf7raeuz2kc534

Using Local Grammar for Entity Extraction from Clinical Reports

Aicha Ghoulam, Fatiha Barigou, Ghalem Belalem, Farid Meziane
2015 International Journal of Interactive Multimedia and Artificial Intelligence  
Information Extraction (IE) is a natural language processing (NLP) task whose aim is to analyze texts written in natural language to extract structured and useful information such as named entities and  ...  Hence, a system for extracting this information in a structured form can benefits healthcare professionals.  ...  of an ensemble learning-based approach and a Vector Space Model based method for disorder entity encoding.  ... 
doi:10.9781/ijimai.2015.332 fatcat:i7q5tilqk5cozds5vz4b4eyqgq

Extracting Temporal Entity from Urdu Language Text

Daler Ali, Malik Muhammad Saad Missen, Muhammad Ali Memon, Muhammad Ali Nizamani, Asadullah Shaikh
2020 University of Sindh Journal of Information and Communication Technology  
In this paper, we propose a rule-based approach for temporal entity extraction for Urdu language.  ...  However, research for Urdu language lags far behind and there is a need for lot of work to be done in this regard especially when huge quantity of Urdu data is being generated on online social networks  ...  A sequencer system developed for analysis of temporal entities [21] existing in news articles and user generated unstructured contents.  ... 
doaj:388be7e81ab64e0c9cc849d17b0d6820 fatcat:hbgyud3nwbfu7k6dlt2s42fyo4

A hybrid model of sentimental entity recognition on mobile social media

Zhibo Wang, Xiaohui Cui, Lu Gao, Qi Yin, Lei Ke, Shurong Zhang
2016 EURASIP Journal on Wireless Communications and Networking  
In this paper, a hybrid sentimental entity recognition model (HSERM) has been designed.  ...  It provides us a data source that we can use to extract peoples' opinions which are important for product review and public opinion monitoring.  ...  Finally, combining some rules, the names could be recognized automatically. Turkish scholars [12] did the named-entity recognition on their domestic twitter.  ... 
doi:10.1186/s13638-016-0745-7 fatcat:kvghtwvi3bdltpkeiuwckkl2ry

A Survey of Code-switched Speech and Language Processing [article]

Sunayana Sitaram, Khyathi Raghavi Chandu, Sai Krishna Rallabandi, Alan W Black
2020 arXiv   pre-print
We motivate why processing code-switched text and speech is essential for building intelligent agents and systems that interact with users in multilingual communities.  ...  This survey reviews computational approaches for code-switched Speech and Natural Language Processing.  ...  Named Entity Recognition (NER) Named Entity Recognition (NER) datasets for code-switching are similar to LID datasets, with word-level annotations. • A shared task was organized to address NER for code-switched  ... 
arXiv:1904.00784v3 fatcat:r5tsg4kdnfbtnndae523c32pta

Extraction and Analysis of Social Networks Data to Detect Traffic Accidents

Nestor Suat-Rojas, Camilo Gutierrez-Osorio, Cesar Pedraza
2022 Information  
The second consists of vectorially representing the messages and classifying them as accidents or non-accidents. The third phase uses named entity recognition techniques to detect the location.  ...  Social network mining has emerged as a low-cost alternative. However, social networks come with several challenges such as informal language and misspellings.  ...  Furthermore, a thank you to the Programming Languages and Systems (PLaS) research group for their feedback on the work.  ... 
doi:10.3390/info13010026 fatcat:nexem2bl4vcm3evk5thtzjl4we

WLV-RIT at SemEval-2021 Task 5: A Neural Transformer Framework for Detecting Toxic Spans [article]

Tharindu Ranasinghe, Diptanu Sarkar, Marcos Zampieri, Alexander Ororbia
2021 arXiv   pre-print
In recent years, the widespread use of social media has led to an increase in the generation of toxic and offensive content on online platforms.  ...  Furthermore, we develop an open-source framework for multilingual detection of offensive spans, i.e., MUDES, based on neural transformers that detect toxic spans in texts.  ...  Acknowledgments We would like to thank the shared task organizers for making this interesting dataset available. We further thank the anonymous SemEval reviewers for their insightful feedback.  ... 
arXiv:2104.04630v3 fatcat:2uqhyrjudbbr5jwgnljqnieslu

ANEC: An Amharic Named Entity Corpus and Transformer Based Recognizer [article]

Ebrahim Chekol Jibril, A. Cüneyd Tantğ
2022 arXiv   pre-print
Named entity recognition enables the identification of proper names as well as temporal and numeric expressions in an open domain text.  ...  In this paper, we present an Amharic named entity recognition system based on bidirectional long short-term memory with a conditional random fields layer.  ...  On the other hand, rule-based systems generally perform quite well in the identification of temporal and numerical expressions.  ... 
arXiv:2207.00785v1 fatcat:z76zwhd25fazjnybuftvl3paii

Towards Generalizable Place Name Recognition Systems

Arda Akdemir, Ali Hürriyetoğlu, Erdem Yörük, Burak Gürel, Çağri Yoltar, Deniz Yüret
2018 Proceedings of the 12th Workshop on Geographic Information Retrieval - GIR'18  
Most of the previous work done on entity recognition for English makes use of similar corpora for both training and testing.  ...  Place name recognition is one of the key tasks in Information Extraction. In this paper, we tackle this task in English News from India.  ...  ACKNOWLEDGEMENTS We thank our team members for their feedbacks and suggestions regarding this paper.  ... 
doi:10.1145/3281354.3281363 dblp:conf/gis/AkdemirHYGYY18 fatcat:7abmfcqofnck5kq7gtuxxzngvi

Systematic Review on Implicit and Explicit Aspect Extraction in Sentiment Analysis

Jaafar Zubairu Maitama, Norisma Idris, Asad Abdi, Liyana Shuib, Rosmadi Fauzi
2020 IEEE Access  
NLP-based [92, 93] exploits NLP-based resources mainly named entity recognition that includes a stop words list, linguistic knowledge base, sentiment lexicons, and general-purpose natural language processing  ...  Generally, SA is being investigated based on three ranks, namely: document, sentence, and aspect [1] .  ...  Apart from that, he also actively appeared in the mass media, a writer for local newspapers and an invited speaker on political, social, economic and current issues in the country.  ... 
doi:10.1109/access.2020.3031217 fatcat:vosmjncbe5h6lfaoucmjy2yxq4

Challenges, Techniques, and Trends of Simple Knowledge Graph Question Answering: A Survey

Mohammad Yani, Adila Alfa Krisnadhi
2021 Information  
Simple questions are the most common type of questions used for evaluating a knowledge graph question answering (KGQA).  ...  In this paper, we present a comprehensive survey of answering simple questions to classify available techniques and compare their advantages and drawbacks in order to have better insights of existing issues  ...  Task Caption Input Output Used in Named entity recognition To classify tokens accord- ing to a class Text NER Entity and relation linking Extractive question answer- ing To extract an answer  ... 
doi:10.3390/info12070271 fatcat:so5vmq7pkbdj3alkfnxf6xjchq
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