[PDF] Top 20 Named Entity Recognition without Gazetteers

... In Proceedings of the 36th Annual Meeting of the Association for Computational Linguistics and Proceedings of the 17th International Conference on Compu- tational Linguistics, pages 848-[r] ... See full document

... We propose using large-scale clustering of de- pendency relations between verbs and multi- word nouns (MNs) to construct a gazetteer for named entity recognition (NER). Since depen- dency relations ... See full document

... for named entity recognition have been purely data-driven, with a strong emphasis on get- ting rid of the efforts for collecting external resources or designing hand-crafted ...external ... See full document

... (e.g. a Wikipedia title), and an entity type. While these tags have a correct type assigned for at least one context, they are not aligned to phrases in the text, and may not share the same form as all of their ... See full document

... of named-entities, but we present a technique that can exploit diverse types of text, including text without proper grammatical sentences, such as tables and lists (marked up with ... See full document

... Named entity recognition (NER) is a challenging learning problem. One the one hand, in most lan- guages and domains, there is only a very small amount of supervised training data available. On the ... See full document

... Since the goal of NER is to recognize instances of named entities in running text, it is established practice to treat NER as a “word-by-word sequence labeling task” (Jurafsky and Martin, 2009). There are two ... See full document

... (Named Entity Rule Language)[17] was ...for named entity ...or named entity (IntConcept for short) by applying a NERL rule on the input text and zero or more previously defined ... See full document

... Rule Based approach is time consuming task to develop any NER system. Rule based approach is used only when you know the target language well and have sufficient knowledge about the linguistic rules like knowledge of ... See full document

... Not much work has been done in NER in Telugu and other Indian languages so far. In this paper, we have reported our work on Named Entity Recogni- tion for Telugu. We have developed a CRF based noun tagger, ... See full document

... Gazetteers for Named Entity Recognition by Large- Scale Clustering of Dependency Relations. In Pro- ceedings of the 46th Annual Meeting of the Association for Computational Linguistics (ACL), ... See full document

... 2016), named entity recognition (Ma and Hovy, 2016), and semantic role labeling (He et ...i.e. without recurring either to linguistic features or to external knowledge sources ...of ... See full document

... monolingual named entity annotated data (NE-mono) is necessary to train a monolingual NER ...tagger. Named entity annotated bitext (NE-bitext) is used to evaluate our bilingual ... See full document

... Often the phonetic inconsistencies in English lead to low matching score for two representation of the same name. To take this into account, before matching the two strings the named entity retrieved from ... See full document

... Named-Entity Recognition (NER) is still a challenging task for languages with low digital re- sources. The main difficulties arise from the scarcity of annotated corpora and the consequent ... See full document

... a named entity ...the named en- tity for the current word is ...an entity, there will be a bi- nary rule applied where one word will be under the left child and the other word will be under ... See full document

... The second batch of documents was a group of sentences in which a sentence context is not suffi- cient to designate a NE, so we need to know more about the particular NE, e.g. we need to look for its co-references in the ... See full document

... as Named Entity Recognition (NER) and it is one of the fundamental tasks in natural language pro- cessing ...extracted named entities can benefit various subsequent NLP tasks, including ... See full document

... In this paper, we present a novel recurrent network-based model for nested named entity recognition and nested entity mention detection. We propose a hypergraph representation for this problem ... See full document

... A mention containing a single word requires three actions to be considered: T RANSITION (a), S HIFT and R EDUCE (a). Using this approach, we can model consecutive transitions of different mentions, multiple hierarchical ... See full document