Abstract In this work, we examine the ability of NER models to use contextual information when predicting type an ambiguous entity. We introduce NRB, a new testbed carefully designed diagnose Name Regularity Bias models. Our results indicate that all state-of-the-art tested show such bias; BERT fine-tuned significantly outperforming feature-based (LSTM-CRF) ones on despite having comparable (so...

In the current study at this paper, the different approaches of developing one NER system is discussed. This paper discuss related work about Name Entity Recognition System in English Language. A little database collection of 200 sentences contains 3080 words. The features selection and generations are suggested to capture the Name Entity. The proposed work is expected to predict the Name Entit...

Xinjiang multi-nationality name entity recognition is an important part in multi-language processing. In this paper, we analyze the patterns of Uighur and Kazak person names, and perform the name identity recognition using rule-based approach. We also propose and implement the rules for Uighur and Kazak word segmentation.

In this paper, we propose a new method, association rules mining for Named Entity Recognition (NER) and co-reference resolution. The method uses several morphological and lexical features such as Pronoun Class (PC) and Name Class (NC), String Similarity (SP) and Position (P) in the text, into a vector of attributes. Applied to a corpus of newspaper in the Indonesian language, the method outperf...

The more Chinese language materials come out, the more we have to focus on the “same personal name” problem. In our personal name disambiguation system, the hierarchical agglomerative clustering is applied, and named entity is used as feature for document similarity calculation. We propose a two-stage strategy in which the first stage involves word segmentation and named entity recognition (NER...

Proper name recognition is a subtask of Name Entity Recognition in Message Understanding Conference. For our corpus annotation proper name recognition is a crucial task since proper names appear approximately in more than 50% of total sentences of the electronic texts that we collected for such purpose. Our work is focused on composite proper names (names with coordinated constituents, names wi...

This project is involved with extraction and transliteration of entity names between languages that use different writing systems (or alphabets). Extraction involves the automatic identification of sequences in parallel/comparable corpora/text that can be considered as proper entity names. On the other hand, transliteration generation involves automatic transformation of a source language name ...