[PDF] Top 20 Exploiting Domain Structure for Named Entity Recognition

... Named Entity Recognition (NER) is a fundamental task in text mining and nat- ural language ...training domain, but they tend to adapt poorly to slightly different ...for exploiting the ... See full document

... relevant entity for follow-up questions and ig- nore extraneous entities which may have been misclassi- ...an entity can be more detri- mental to a conversation than over-classifying ...an entity to ... See full document

... of Named Entities (NEs) in many natural language processing tasks, there has been a lot of work aimed at developing accurate named entity extractors (Borthwick, 1999; Velardi et ... See full document

... Intuitively, a NERL rule creates an intermediate con- cept or named entity (IntConcept for short) by ap- plying a NERL rule on the input text and zero or more previously defined intermediate concepts. NERL ... See full document

... in Named Entity Recognition (NER) can outperform existing approaches that handle non-local dependencies, while be- ing much more computationally ...distance structure present in ... See full document

... entertainment domain transfer, although many NE triggers ...son entity often appear as the subject of “visited”, “said”, etc, or are modified by “excellent”, “popu- lar”, “famous” ... See full document

... as we refine the application of constraints. The baseline CRF classifier has modest precision but much weaker recall and misses a number of vari- able A and B entities entirely. We are not partic- ularly concerned about ... See full document

... We downloaded the text files of a subset of PMC documents that are available at ftp://ftp.ncbi.nlm.nih.gov/pub/pmc in May 2018, and picked 3960 full-text documents that had a Medical Subject Heading (Mesh) term ’cancer’. ... See full document

... Multi-Grained Named Entity Recognition where multiple entities or en- tity mentions in a sentence could be non- overlapping or totally ...recognize named entities without ex- plicitly assuming ... See full document

... Natural Language processing refers to the use and ability of systems to process sentences in a natural language such as English, Telugu rather than in a specialized artificial computer language such as C, C++, java ... See full document

... In our work, we used 100 dimensional word em- beddings pre-trained with structured skip-gram on the Gigaword corpus (Ling et al., 2015). These were concatenated with 50 dimensional charac- ter embeddings obtained using a ... See full document

... tion of domain specific knowledge about enti- ties from AFP corpora must circumvent this lack of indications. In this perspective we use an implementation of a naive linker described in (Stern and Sagot, 2010). ... See full document

... Robust cross-domain generalization is key in many NLP applications. In addition to surface and linguis- tic differences, differences in world knowledge pose a key challenge, e.g., the fact that Java refers to a ... See full document

... each named en- tity corresponding to a phrase in the tree, along with a root node which connects the entire sen- ...syntactic structure is rep- ...a named entity ... See full document

... treat named-entity recognition as a sequence tagging problem, where each word is tagged with its entity type if it is part of an ...and domain and no expert knowledge is ... See full document

... The most problematic aspects of identifying NEs according to the protocols as defined by Tjong Kim Sang and De Meulder (2003) and the above principles is that there are a number of edge cases that are extremely difficult ... See full document

... to domain adap- tation is to consider that the instances from the source and the target domain are drawn from dif- ferent ...source domain training data, so as to adapt the source domain data ... See full document

... In each case, each item (abstract, article or e-mail) was tokenized and each token was hand-labeled as either being part of a name (protein or person) or not, respectively. We used a standard natural lan- guage toolkit ... See full document

... the authors followed a statistical approach (HMMs) for NER task together with some other Information Extraction related tasks. In order to deal with the agglutinative structure of the Turkish, the authors worked ... See full document

... Table 5 shows the performance of these mod- els. The results for (A) and (C) indicate that the matching information alone does not improve ac- curacy. This is because entity regions can be iden- tified fairly ... See full document