[PDF] Top 20 Aligning Knowledge and Text Embeddings by Entity Descriptions
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Aligning Knowledge and Text Embeddings by Entity Descriptions
... and Text Jointly Embedding Wang et al. (2014a) 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 hence ... See full document
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A Sequence Learning Method for Domain Specific Entity Linking
... texts for the mention detection and aims on-the- fly annotation of short texts using agreement ap- proach based on Wikipedia link structure. More- over, these approaches focus on global coherence approaches that ... See full document
8
Improving Distantly Supervised Relation Extraction with Joint Label Embedding
... from entity descriptions with a gating mech- anism to learn label embeddings, while avoiding the imposed noise (highlighted in green) in entity descriptions with an attention ...label ... See full document
9
Building Compact Entity Embeddings Using Wikidata
... build entity representations. Then anchors are used to aligning them into the same space as word ...learns entity representations using their example occurrences in a large text corpus ... See full document
9
Entity Disambiguation by Knowledge and Text Jointly Embedding
... most entity disambiguation systems, the secret recipes are feature representa- tions for mentions and entities, most of which are based on Bag-of-Words (BoW) ...embedding knowledge base and text in ... See full document
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Bridge Text and Knowledge by Learning Multi Prototype Entity Mention Embedding
... In this paper, we propose a novel Multi- Prototype Mention Embedding (MPME) model, which jointly learns the representations of words, entities, and mentions at sense level. Different mention senses are distinguished by ... See full document
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Aligning Entity Names with Online Aliases on Twitter
... real entity names. Many research appli- cations rely on identifying entity names in text, but people often refer to entities with unexpected nicknames and ...to knowledge base entries, like a ... See full document
11
Zero Shot Entity Linking by Reading Entity Descriptions
... prior entity linking task definitions and compared them to our task in section ...related entity linking models and unsupervised domain adaptation methods. Entity linking models Entity linking ... See full document
12
Type Sensitive Knowledge Base Inference Without Explicit Type Supervision
... loss. Entity embeddings are unit normalized at the end of every epoch, for the type ...the embeddings of the base model to unit norm performs better than using L2 ...our knowledge, the results ... See full document
6
World Knowledge for Reading Comprehension: Rare Entity Prediction with Hierarchical LSTMs Using External Descriptions
... world knowledge, previous data sets and tasks for reading compre- hension have targeted other aspects of the read- ing comprehension problem, at times explicitly at- tempting to factor out its ...anonymized ... See full document
10
Knowledge Enhanced Contextual Word Representations
... unlabeled text, do not contain any explicit grounding to real world entities and are often unable to remember facts about those ...multiple knowledge bases (KBs) into large scale models, and thereby enhance ... See full document
12
Improving Neural Entity Disambiguation with Graph Embeddings
... of Entity Linking (EL) (Shen et ...biguous entity mention/span in a context and an entity in a knowledge ...Name Entity Recognition (NER) (Nadeau and Sekine, 2007) finds entity ... See full document
8
Mining Entity Synonyms with Efficient Neural Set Generation
... Another line of work divides the synonym set discovery problem into two sequential subtasks: (1) synonymy detection (i.e., finding term pairs of synonymy relation), and (2) syn- onymy organization (i.e., aggregating ... See full document
8
Merging Verb Senses of Hindi WordNet using Word Embeddings
... word embeddings for gloss similar- ity computation and compare with various WordNet based gloss similarity ...word embeddings show significant improvement over Word- Net based ... See full document
9
Aligning Multilingual Word Embeddings for Cross Modal Retrieval Task
... In Table 1 and 2, we show the results for English and German captions. For English captions, we see 21.28% improvement on average compared to Kiros et al. (2014). There is a 1.8% boost on aver- age compared to Mono due ... See full document
7
An Entity Focused Approach to Generating Company Descriptions
... reading text from the web and extracting those sentences which con- tain pairs in the seed ...the entity, while the words around them form the pattern (the words between the tags are selected as well as ... See full document
6
Literature Review on Fuzzy Score Based Short Text Understanding from Corpus Data Using Semantic Discovery
... short text to a set of concepts as a mechanism of an understanding ...human-crafted knowledge bases that map instances to ...probabilistic knowledge base, develop a corpus-based framework for ... See full document
6
Identification and Verification of Simple Claims about Statistical Properties
... cation was population, for which the relatively few errors were due to the patterns learned not being able to distinguish between different types of pop- ulation e.g. general vs working population. On the other hand, the ... See full document
6
Pooled Contextualized Embeddings for Named Entity Recognition
... Future work. Our pooling operation makes the conceptual simplification that all previous in- stances of a word are equally important. However, we may find more recent mentions of a word - such as words within the same ... See full document
5
Domain Adaptable Hybrid Generation of RDF Entity Descriptions
... Generation meta-systems which can be automa- tically adapted to a new domain have been explo- red in recent years. Angeli et al. (2010) learn to make decisions about content selection and (se- parately) template ... See full document
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