entity identification
Think Globally, Apply Locally: Using Distributional Characteristics for Hindi Named Entity Identification
... need entity identification in large cor- ...Named Entity Identification (CLGIN) which combines the global characteristics with the local context for Hindi Named Entity ...Named ...
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NAMED ENTITY IDENTIFICATION AND CLASSIFICATION USING MACHINE LEARNING TECHNIQUES
... Named Entity Identification and Classification Using Machine Learning Techniques for Telugu ...Named Entity Recognition (NER).Named Entity Recognition is a task in which entities like proper ...
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Named Entity Identification and Classification in Telugu Using Knowledge Base Approach
... Named Entity Recognition (NER) is an Information Extraction task that has become an integral part of many other Natural Language Processing (NLP) tasks, such as Machine Translation and Information Retrieval Part ...
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Discriminative Training of Clustering Functions: Theory and Experiments with Entity Identification
... the entity identification problem, where a pairwise classifier (LMR) is trained us- ing the SNoW learning architecture (Roth, 1998) based on variations of Perceptron and Winnow, and using a col- lection of ...
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A Class-based Language Model Approach to Chinese Named Entity Identification
... named entity (NE) identification using a class-based language model ...NE identification concentrates on three types of NEs, namely, personal names (PERs), location names (LOCs) and organization ...
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A Review on Rule Based Entity Identification for Data Cleaning
... linkage, entity identification or entity resolution (ER) to analyze the records referring to the same real-world ...entity. Entity resolution can also be referred as object matching, ...
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Chinese Named Entity Identification Using Class based Language Model
... problem using Viterbi algorithm. In general, current approaches to NE identification (e.g. Chen, 1997) usually contain two separate steps: word segmentation and NE identification. The word segmentation ...
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Entity Identification as Multitasking
... in the number of types (assuming exact decoding with first-order label dependency). We empha- size that the asymptotic runtime remains quadratic even if we heuristically prune previous labels based on the BIO scheme. ...
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Scalable graph based method for individual named entity identification
... Ontology: In this paper, our definition of an on- tology is represented as a tree of entity types. In the following, the variable T represents the total number of nodes of this tree minus one (we don’t count the ...
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Language Independent Named Entity Identification using Wikipedia
... NER systems so far developed involved linguistic grammar-based techniques as well as statistical models. The grammar-based techniques require linguistic expertise and requires strenuous efforts to build a NER system for ...
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Twitter Named Entity Extraction and Linking Using Differential Evolution
... Named Entity Identification Twitter named entities are first extracted using a supervised machine learning approach, namely CRF in a Differential Evolution (DE) ...
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Family history information extraction via deep joint learning
... (1) entity identification, identifying family members and their observations (diseases) mentioned in clinical text; (2) family history extraction, extracting side of family of family members, living status ...
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Language Identification and Named Entity Recognition in Hinglish Code Mixed Tweets
... are bilingual, or even trilingual, and their tweets can be monolingual in English or their vernacular, or code-mixed. Past research has looked at multi- ple dimensions of this behaviour such as its rela- tionship to ...
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TEXT MINING WITH ENRICHED TEXT FOR ENTITY ORIENTED RETRIEVAL AND TEXT CLUSTERING
... order to return them as search answers or to extract entity relations. Similarly, locating and modelling NE as features is a critical step in text clustering as many NEs describe the main topic of a document. ...
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Character Identification on Multiparty Conversation: Identifying Mentions of Characters in TV Shows
... an entity linking task, called character identification, that maps each men- tion in multiparty conversation to its referent char- ...for entity linking using such ...
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Chinese Event Coreference Resolution: An Unsupervised Probabilistic Model Rivaling Supervised Resolvers
... both entity and event coreference ...the identification of anaphoric event mentions challeng- ing even in a supervised manner, let alone in an un- supervised ...
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Entity Retrieval via Entity Factoid Hierarchy
... an entity factoid hi- erarchy summarizes all the descriptions regarding an entity, which is similar to the “entity pseudo- document” used in some existing entity retrieval ...Each ...
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KVQA: Knowledge-Aware Visual Question Answering
... named entity linking where the task is to link the named entity appearing in an image to one of the entities in ...named entity linking, we also provide a support set contain- ing reference images of ...
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Going out on a limb: Joint Extraction of Entity Mentions and Relations without Dependency Trees
... Recently, Miwa and Bansal (2016) proposed an end-to-end LSTM based sequence and tree- structured model. They extract entities via a se- quence layer and relations between the entities via the shortest path dependency ...
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Factorizing Complex Models: A Case Study in Mention Detection
... The simplest model which can be considered for the task is to create an atomic tag by “gluing” to- gether the sub-task labels and considering the new label atomic. This method transforms the prob- lem into a regular ...
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