Results 1 - 10 of 1,898

Unsupervised Models for Named Entity Classification

by Michael Collins, Yoram Singer - In Proceedings of the Joint SIGDAT Conference on Empirical Methods in Natural Language Processing and Very Large Corpora , 1999
"... This paper discusses the use of unlabeled examples for the problem of named entity classification. A large number of rules is needed for coverage of the domain, suggesting that a fairly large number of labeled examples should be required to train a classifier. However, we show that the use of unlabe ..."
Abstract - Cited by 542 (4 self) - Add to MetaCart
This paper discusses the use of unlabeled examples for the problem of named entity classification. A large number of rules is needed for coverage of the domain, suggesting that a fairly large number of labeled examples should be required to train a classifier. However, we show that the use

Weakly supervised named entity classification

by Edouard Grave
"... In this paper, we describe a new method for the problem of named entity classifica-tion for specialized or technical domains, using distant supervision. Our approach relies on a simple observation: in some specialized domains, named entities are almost unambiguous. Thus, given a seed list of names o ..."
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In this paper, we describe a new method for the problem of named entity classifica-tion for specialized or technical domains, using distant supervision. Our approach relies on a simple observation: in some specialized domains, named entities are almost unambiguous. Thus, given a seed list of names

UNSUPERVISED ENTITY CLASSIFICATION WITH WIKIPEDIA AND WORDNET

by unknown authors
"... The task of classifying entities appearing in textual annotations to an arbitrary set of classes has not been extensively researched, yet it is useful in multimedia retrieval. We proposed an unsupervised algorithm, which expresses entities and classes as Wordnet synsets and uses Lin measure to class ..."
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The task of classifying entities appearing in textual annotations to an arbitrary set of classes has not been extensively researched, yet it is useful in multimedia retrieval. We proposed an unsupervised algorithm, which expresses entities and classes as Wordnet synsets and uses Lin measure

Unsupervised Named Entity Classification Models

by And Their Ensembles, Jae-ho Kim, In-ho Kang, Key-sun Choi - Proceedings of the 19th international conference on Computational linguistics , 2002
"... This paper proposes an unsupervised learning model for classifying named entities. This model uses a training set, built automatically by means of a small-scale named entity dictionary and an unlabeled corpus. This enables us to classify named entities without the cost for building a large ha ..."
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This paper proposes an unsupervised learning model for classifying named entities. This model uses a training set, built automatically by means of a small-scale named entity dictionary and an unlabeled corpus. This enables us to classify named entities without the cost for building a large

K.: Unsupervised Named Entity Classification Models and their Ensembles

by Jae-ho Kim, In-ho Kang, Key-sun Choi - In: Proceedings of the 19th Conference on Computational Linguistics. (2002
"... This paper proposes an unsupervised learning model for classifying named entities. This model uses a training set, built automatically by means of a small-scale named entity dictionary and an unlabeled corpus. This enables us to classify named entities without the cost for building a large hand-tagg ..."
Abstract - Cited by 11 (0 self) - Add to MetaCart
This paper proposes an unsupervised learning model for classifying named entities. This model uses a training set, built automatically by means of a small-scale named entity dictionary and an unlabeled corpus. This enables us to classify named entities without the cost for building a large hand

A sequencing model for situation entity classification

by Alexis Palmer, Elias Ponvert, Jason Baldridge, Carlota Smith - In Annual Meeting of the Association of Computational Linguistics (ACL , 2007
"... Situation entities (SEs) are the events, states, generic statements, and embedded facts and propositions introduced to a discourse by clauses of text. We report on the first datadriven models for labeling clauses according to the type of SE they introduce. SE classification is important for discours ..."
Abstract - Cited by 8 (1 self) - Add to MetaCart
Situation entities (SEs) are the events, states, generic statements, and embedded facts and propositions introduced to a discourse by clauses of text. We report on the first datadriven models for labeling clauses according to the type of SE they introduce. SE classification is important

A Sequential Algorithm for Training Text Classifiers

by David D. Lewis, William A. Gale , 1994
"... The ability to cheaply train text classifiers is critical to their use in information retrieval, content analysis, natural language processing, and other tasks involving data which is partly or fully textual. An algorithm for sequential sampling during machine learning of statistical classifiers was ..."
Abstract - Cited by 631 (10 self) - Add to MetaCart
grouping of textual or partially textual entities. Document retrieval, categorization, routing, filtering, and clustering, as well as natural language processing tasks such as tagging, word sense disambiguation, and some aspects of understanding can be formulated as text classification. As the amount

Towards large-scale, open-domain and ontology-based named entity classification

by Johanna Völker - In Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP’05 , 2005
"... ..."
Abstract - Cited by 43 (7 self) - Add to MetaCart
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A Bootstrapping Approach to Named Entity Classification Using Successive Learners

by Cheng Niu, Wei Li, Jihong Ding, Rohini K. Srihari - In Proceedings of the 41st Annual Meeting of the ACL , 2003
"... approach to named entity (NE) classification. This approach only requires a few common noun/pronoun seeds that correspond to the concept for the target NE type, e.g. he/she/man/woman for PERSON NE. The entire bootstrapping procedure is implemented as training two successive learners: (i) a de ..."
Abstract - Cited by 14 (2 self) - Add to MetaCart
approach to named entity (NE) classification. This approach only requires a few common noun/pronoun seeds that correspond to the concept for the target NE type, e.g. he/she/man/woman for PERSON NE. The entire bootstrapping procedure is implemented as training two successive learners: (i) a

Using unlabeled MEDLINE abstracts for biological named entity classification

by Manabu Torii, K. Vijay-shanker - In: Proceedings of genome informatics workshop , 2002
"... Named Entity Recognition is a crucial step for Information Extraction from biological texts. By using surface clues such as capitalization, numbers, and special symbols, existing tools extract names of protein and other biological entities well. However, names of different entities share surface cha ..."
Abstract - Cited by 4 (1 self) - Add to MetaCart
Named Entity Recognition is a crucial step for Information Extraction from biological texts. By using surface clues such as capitalization, numbers, and special symbols, existing tools extract names of protein and other biological entities well. However, names of different entities share surface
Results 1 - 10 of 1,898