[PDF] Top 20 Named Entity Disambiguation in Streaming Data
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Named Entity Disambiguation in Streaming Data
... a data acquisition bottleneck, since the creation of a training corpus requires skilled human annotators to manually inspect the ...the entity name is ambiguous, the sense of messages that are posted in ... See full document
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“One Entity per Discourse” and “One Entity per Collocation” Improve Named Entity Disambiguation
... single entity per document, but given the need to find occurrences for different entities, the organizers (Ji et ...all named-entities occurring in the target ...one entity per collection would also ... See full document
10
A Feature Induction Algorithm with Application to Named Entity Disambiguation
... necessary data structures for evaluation of MI, IG, SU and FT scores, which takes O(pKN ) ...The data structures esentially store the counts of samples in each class, for each ... See full document
7
A Joint Chinese Named Entity Recognition and Disambiguation System
... We also use a small test set within 6 test names, which is released by the Second CIPS- SIGHAN. The results in Table 3 show that the proposed method gives an average precision of 74.41%. However, the recall value is not ... See full document
6
AIDArabic A Named Entity Disambiguation Framework for Arabic Text
... This observation confirms our initial hypothe- sis that lack of data is one of the main challenges for applying NED on Arabic text. Another aspect that harms recall is the nature of Arabic language. Letters get ... See full document
9
Multimodal Named Entity Disambiguation for Noisy Social Media Posts
... Figure 3: Deep Levenshtein, which predicts approximate Levenshtein scores between two strings. As a byproduct of this model, the shared Bi-LSTM can produce lexical embeddings purely based on lexical property of character ... See full document
9
GerNED: A German Corpus for Named Entity Disambiguation
... We present the results of our baseline Entity Linking system in Tables 6 and 7. Table 6 shows the micro-averaged accu- racy (MAA) and Bˆ3+ scores for all queries, KB queries only, and NIL queries only. The ... See full document
8
Personalized Page Rank for Named Entity Disambiguation
... of Named Entity Disambiguation is to map entity mentions in the document to their correct entries in some knowledge ...for disambiguation and ef- fectively filters out noise introduced ... See full document
6
Classifying Relations for Biomedical Named Entity Disambiguation
... The named entity disambiguation task is defined as follows: given a mention of a named entity in text, we automatically assign a semantic tag d to it, where d ∈ D, and D is a ... See full document
10
diaNED: Time Aware Named Entity Disambiguation for Diachronic Corpora
... 13,773 entity mentions and randomly selected 350 of ...all entity mentions in re- spective sentences with their Wikipedia ...gold entity mentions in 334 ... See full document
8
Named Entity Disambiguation for little known referents: a topic based approach
... for named entity disambiguation in previous ...at data with authors and try to determine the number of individual authors and link them to their corresponding ...same entity, but look ... See full document
12
Building a Multilingual Lexical Resource for Named Entity Disambiguation, Translation and Transliteration
... 4.3. Multilingual Approach: Context Datasets For English and for each of the languages mentioned in subsection 4.2., a DisDict and a Context Dataset were cre- ated. Table 3 shows the number of NE contexts extracted from ... See full document
8
Learning Text Representations for 500K Classification Tasks on Named Entity Disambiguation
... From another perspective, a set of 500K clas- sification problems provides a great experimen- tal framework for testing text representation and classification algorithms. More specifically, deep learning methods provide ... See full document
10
Enhancing Retrieval of Geological Text using Named Entity Disambiguation
... This algorithm begins at the root node of co- occurrence graph, explores the neighbouring nodes and expands the query using them. For example. if the Currentnode is West Bengal, the GEOQUERY is expanded with Calcutta, ... See full document
10
Joint Learning of the Embedding of Words and Entities for Named Entity Disambiguation
... log data, and consists of a training and a test set containing 1,043 and 1,013 documents, re- ...an entity from (1) the title of the entity, (2) the title of another entity redirect- ing to ... See full document
10
Alleviating Poor Context with Background Knowledge for Named Entity Disambiguation
... Named Entity Disambiguation (NED) al- gorithms disambiguate mentions of named entities with respect to a knowledge-base, but sometimes the context might be poor or ... See full document
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Using Encyclopedic Knowledge for Named entity Disambiguation
... when ranking with cosine similarity is set to the value that gives highest accuracy on training data. As can be seen in the last two columns, the Tax- onomy Kernel significantly outperforms the Co- sine similarity ... See full document
8
Named Entity Disambiguation for Noisy Text
... measure entity- context relatedness using their embeddings (Ya- mada et ...Noisy Data Chisholm and Hachey (2015) showed that despite the noisy nature of web data, augmenting Wikipedia-derived ... See full document
11
Large Scale Named Entity Disambiguation Based on Wikipedia Data
... Wikipedia entity pages and we discarded their content during the informa- tion extraction ...a disambiguation for ...a disambiguation page, probably because the origi- nal pages changed over time, ... See full document
9
A comparison of Named Entity Disambiguation and Word Sense Disambiguation
... test data each year since 2009. We use the development and test data available in the 2010 task (TAC10 for short), which includes examples from news and the ...same entity, even if us- ing a ... See full document
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