[PDF] Top 20 Entity Disambiguation by Knowledge and Text Jointly Embedding
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Entity Disambiguation by Knowledge and Text Jointly Embedding
... an entity disambiguation method is commonly composed of three ...for disambiguation models based on the represen- tations of mentions and entities constructed in stage ...the disambiguation ... 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
10
Structural Semantic Relatedness: A Knowledge Based Method to Named Entity Disambiguation
... employing knowledge sources to enhance the named entity ...semantic knowledge for computing the similarity between name ...named entity disambiguation, where similari- ty is computed ... See full document
10
Using Encyclopedic Knowledge for Named entity Disambiguation
... human knowledge available in Wikipedia, a free online encyclopedia created through decentralized, collective efforts of thou- sands of users (Remy, ...the entity disambiguation ...named entity ... See full document
8
Entity Disambiguation for Knowledge Base Population
... extracted knowledge into a KB is fraught with challenges arising from nat- ural language ambiguity, textual inconsistencies, and lack of world ...con- text may reveal it to be the 43rd president, George ... See full document
9
Knowledge Graph and Text Jointly Embedding
... show jointly embedding brings promising improve- ments to the accuracy of predicting facts, com- pared to separately embedding the knowledge graph and the text corpus, ...larly, ... See full document
11
Joint Learning of the Embedding of Words and Entities for Named Entity Disambiguation
... Named Entity Disambiguation (NED) refers to the task of resolving multiple named entity mentions in a document to their correct references in a knowledge base (KB) ...novel embedding ... See full document
10
Learning Entity Representation for Entity Disambiguation
... or disambiguation has recently re- ceived much attention in natural language process- ing community (Bunescu and Pasca, 2006; Han et ...in knowledge base construction (Ji and Grishman, 2011) like populating ... See full document
5
Exploring Entity Relations for Named Entity Disambiguation
... Typical approaches to NED combine the use of document context knowledge with entity informa- tion stored in the KB in order to disambiguate en- tities. Many systems represent document context and KB ... See full document
6
A Prospective Analysis On Entity Linking For Domain Specific With Heterogeneous Information Networks
... focused entity linking in ...with entity popularity model and entity object model along with knowledge population algorithm, if the network information was ...the knowledge of ... See full document
8
AIDArabic A Named Entity Disambiguation Framework for Arabic Text
... mapping text mentions onto canonical ...an entity-level analytics of these ...the disambiguation of Arabic texts based on an automatically generated knowledge base distilled from ...the ... See full document
9
Aligning Knowledge and Text Embeddings by Entity Descriptions
... and Text Jointly Embedding Wang et ...combines knowledge embed- ding and word embedding in a joint framework so that the entities/relations and words are in the same vector space and ... See full document
6
Jointly Embedding Entities and Text with Distant Supervision
... learn entity embeddings from larger and more diverse data; for example, embeddings learned from Gigaword (which has no entity annotations) outperform embeddings learned on Wikipedia in most of our ...by ... See full document
12
Jointly Embedding Relations and Mentions for Knowledge Population
... Table 2 and 3 illustrate the results of experiments on NELL-50K and NELL-5M, respectively. Both of them show that JRME performs best among all the approaches we implemented. We can also fig- ure out that text ... See full document
6
Jointly Embedding Knowledge Graphs and Logical Rules
... by embedding models, via integer linear pro- gramming or Markov logic ...for entity pairs, and hence fails to discover relations between unpaired ...by jointly modeling knowledge and logic. ... See full document
11
Automatic Selection of Reference Pages in Wikipedia for Improving Targeted Entities Disambiguation
... target entity in a mention is regarded as a node, and the weight of an edge is determined according to con- text similarity, and a prior score of node that is de- termined according to the unique number of ... See full document
5
Learning Text Representations for 500K Classification Tasks on Named Entity Disambiguation
... constant embedding vector, we feed it into the LSTM, and use the last hidden vector h as the context ...con- text representation and 300 dimensional word em- beddings, which are again initialized with the ... See full document
10
Knowledge Enhanced Contextual Word Representations
... raw text, and can encode factual knowl- edge that is difficult to learn from selectional pref- erences either due to infrequent mentions of com- monsense knowledge or long range ...model entity spans ... See full document
12
Representing Text for Joint Embedding of Text and Knowledge Bases
... of knowledge base and textual in- formation was first shown to outperform either source alone in the framework of path-ranking al- gorithms in a combined knowledge base and text graph (Lao et ... See full document
11
Bridge Text and Knowledge by Learning Multi Prototype Entity Mention Embedding
... Entity linking is a core NLP task of identifying the reference entity for mentions in texts. The main difficulty lies in the ambiguity of various en- tities sharing the same mention phrase. Previous work ... See full document
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