CroNER: Recognizing Named Entities in Croatian Using Conditional Random Fields
نویسندگان
چکیده
In this paper we present CroNER, a named entity recognition and classification system for Croatian language based on supervised sequence labeling with conditional random fields (CRF). We use a rich set of lexical and gazetteer-based features and different methods for enforcing document-level label consistency. Extensive evaluation shows that our method achieves state-of-the-art results (MUC F1 90.73%, Exact F1 87.42%) when compared to existing NERC systems for Croatian and other Slavic languages.
منابع مشابه
CroNER: A State-of-the-Art Named Entity Recognition and Classification for Croatian Language
In this paper we present CroNER, a named entity recognition and classification system for Croatian language based on supervised sequence labeling with conditional random fields (CRF). We use a rich set of lexical and gazetteer-based features and different methods for enforcing document-level label consistency. Extensive evaluation shows that our method achieves state-of-the-art results (MUC F1 ...
متن کاملA Novel Approach to Conditional Random Field-based Named Entity Recognition using Persian Specific Features
Named Entity Recognition is an information extraction technique that identifies name entities in a text. Three popular methods have been conventionally used namely: rule-based, machine-learning-based and hybrid of them to extract named entities from a text. Machine-learning-based methods have good performance in the Persian language if they are trained with good features. To get good performanc...
متن کاملRecognizing Named Entities in Tweets
The challenges of Named Entities Recognition (NER) for tweets lie in the insufficient information in a tweet and the unavailability of training data. We propose to combine a K-Nearest Neighbors (KNN) classifier with a linear Conditional Random Fields (CRF) model under a semi-supervised learning framework to tackle these challenges. The KNN based classifier conducts pre-labeling to collect globa...
متن کاملتشخیص اسامی اشخاص با استفاده از تزریق کلمههای نامزد اسم در میدانهای تصادفی شرطی برای زبان عربی
Named Entity Recognition and Extraction are very important tasks for discovering proper names including persons, locations, date, and time, inside electronic textual resources. Accurate named entity recognition system is an essential utility to resolve fundamental problems in question answering systems, summary extraction, information retrieval and extraction, machine translation, video interpr...
متن کاملCombining Proper Name-Coreference with Conditional Random Fields for Semi-supervised Named Entity Recognition in Vietnamese Text
Named entity recognition (NER) is the process of seeking to locate atomic elements in text into predefined categories such as the names of persons, organizations and locations.Most existingNERsystems are based on supervised learning. This method often requires a large amount of labelled training data, which is very time-consuming to build. To solve this problem, we introduce a semi-supervised l...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Informatica (Slovenia)
دوره 37 شماره
صفحات -
تاریخ انتشار 2013