AIDA: An Online Tool for Accurate Disambiguation of Named Entities in Text and Tables
نویسندگان
چکیده
We present AIDA, a framework and online tool for entity detection and disambiguation. Given a natural-language text or a Web table, we map mentions of ambiguous names onto canonical entities like people or places, registered in a knowledge base like DBpedia, Freebase, or YAGO. AIDA is a robust framework centred around collective disambiguation exploiting the prominence of entities, similarity between the context of the mention and its candidates, and the coherence among candidate entities for all mentions. We have developed a Web-based online interface for AIDA where different formats of inputs can be processed on the fly, returning proper entities and showing intermediate steps of the disambiguation process.
منابع مشابه
Extending AIDA framework by incorporating coreference resolution on detected mentions and pruning based on popularity of an entity
Named Entity Disambiguation (NED) is gaining popularity due to its applications in the field of information extraction. Entity linking or Named Entity Disambiguation is the task of discovering entities such as persons, locations, organizations, etc. and is challenging due to the high ambiguity of entity names in natural language text. In this paper, we propose a modification to the existing sta...
متن کاملU-AIDA: a customizable system for named entity recognition, classification, and disambiguation
Recognizing and disambiguating entities such as people, organizations, events or places in natural language text are essential steps for many linguistic tasks such as information extraction and text categorization. A variety of named entity disambiguation methods have been proposed, but most of them focus on Wikipedia as a sole knowledge resource. This focus does not fit all application scenari...
متن کاملAIDA-light: High-Throughput Named-Entity Disambiguation
To advance the Web of Linked Data, mapping ambiguous names in structured and unstructured contents onto knowledge bases would be a vital asset. State-of-the-art methods for Named Entity Disambiguation (NED) face major tradeoffs regarding efficiency/scalability vs. accuracy. Fast methods use relatively simple context features and avoid computationally expensive algorithms for joint inference. Wh...
متن کاملEfficient Entity Disambiguation via Similarity Hashing
The task of Named Entity Disambiguation (NED), which maps mentions of ambiguous names in natural language onto a set of known entities, has been an important issue in many areas including machine translation and information extraction. Working with a huge amount of data (e.g. more than three million entities in Yago), some parts in an NED system which estimate the probability of a mention match...
متن کاملUsing Encyclopedic Knowledge for Named entity Disambiguation
We present a new method for detecting and disambiguating named entities in open domain text. A disambiguation SVM kernel is trained to exploit the high coverage and rich structure of the knowledge encoded in an online encyclopedia. The resulting model significantly outperforms a less informed baseline.
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:
- PVLDB
دوره 4 شماره
صفحات -
تاریخ انتشار 2011