Evaluation of an Algorithm for the Recognition and Classification of Proper Names

@inproceedings{Wakao1996EvaluationOA,
  title={Evaluation of an Algorithm for the Recognition and Classification of Proper Names},
  author={Takahiro Wakao and Robert J. Gaizauskas and Yorick Wilks},
  booktitle={COLING},
  year={1996}
}
We describe an information extraction system in which four classes of naming expressions - organisation, person, location and time names - are recognised and classified with nearly 92% combined precision and recall. The system applies a mixture of techniques to perform this task and these are described in detail. We have quantitatively evaluated the system against a blind test set of Wall Street Journal business articles and report results not only for the system as a whole, but for each… Expand
Using Corpus-derived Name Lists for Named Entity Recognition
TLDR
This paper describes experiments to establish the performance of a named entity recognition system which builds categorized lists of names from manually annotated training data and shows that by using simple filtering techniques for improving the automatically acquired lists, substantial performance benefits can be achieved. Expand
Incremental Recognition and Referential Categorization of French Proper Names
This paper presents Nemesis, a French proper name (PN) recognizer for Large-scale Information Extraction (IE), whose specifications have been elaborated through corpus investigation both in terms ofExpand
Categorizing Dictionary Information for a Lexical Database of Proper Names
mis paper describes the design and development of a lexical database containing about 55,000 records of information about proper nouns and their semantic relationships and odier features obtainedExpand
Resolving Ambiguities in Named Entity Recognition Using Machine Learning
TLDR
A supervised learning algorithm is presented which is used to train the classifier and different combination rules are applied to the data to increase the performance of the model. Expand
Named Entity Recognition in Assamese
TLDR
The main aim of this work is to develop a computational system that can perform NER in text in Assamese, which is a resource poor Indo-Aryan language. Expand
Information Extraction: Beyond Document Retrieval
In this paper we give a synoptic view of the growth of the text processing technology of information extraction (IE) whose function is to extract information about a pre‐specified set of entities,Expand
A Named Entity Recognition System for Dutch
TLDR
A Named Entity Recognition system for Dutch that combines gazetteers, handcrafted rules, and machine learning on the basis of seed material is described and the advantages of using machine learning software as a tool in knowledge acquisition are discussed. Expand
A Hybrid Approach for Named Entity Recognition in Indian Languages
TLDR
A hybrid system that applies Maximum Entropy model (MaxEnt), language specific rules and gazetteers to the task of Named Entity Recognition (NER) in Indian languages designed for the IJCNLP NERSSEAL shared task is described. Expand
Building, Testing, and Applying Concept Hierarchies
TLDR
The formation and presentation of the hierarchy is described along with a study of some of its properties, including a preliminary experiment, which indicates that users may find the hierarchy a more efficient means of locating relevant documents than the classic method of scanning a ranked document list. Expand
Chapter 1 BUILDING , TESTING , AND APPLYING CONCEPT HIERARCHIES
A means of automatically deriving a hierarchical organization of concepts from a set of documents without use of training data or standard clustering techniques is presented. Using a process thatExpand
...
1
2
3
4
5
...

References

SHOWING 1-10 OF 31 REFERENCES
The analysis and acquisition of proper names for robust text understanding
TLDR
This thesis considers the problems that Proper Names cause in the analysis of unedited, naturally-occurring text, and presents a detailed description of the syntax and semantics of seven major classes of Proper Name, and of their surrounding context. Expand
Some Advances in Transformation-Based Part of Speech Tagging
TLDR
A method for expressing lexical relations in tagging that stochastic taggers are currently unable to express is described and how the tagger-can be extended into a k-best tagger, where multiple tags can be assigned to words in some cases of uncertainty. Expand
Building a Large Annotated Corpus of English: The Penn Treebank
TLDR
As a result of this grant, the researchers have now published on CDROM a corpus of over 4 million words of running text annotated with part-of- speech (POS) tags, which includes a fully hand-parsed version of the classic Brown corpus. Expand
The Penn Treebank: Annotating Predicate Argument Structure
TLDR
The implementation of crucial aspects of this new syntactic annotation scheme incorporates a more consistent treatment of a wide range of grammatical phenomena, provides a set of coindexed null elements in what can be thought of as "underlying" position for phenomena such as wh-movement, passive, and the subjects of infinitival constructions. Expand
Proceedings of the Sixth Message Understanding Conference (MUC-6). Morgan Kauf- man
  • Proceedings of the Sixth Message Understanding Conference (MUC-6). Morgan Kauf- man
  • 1995
The Prom Trcel)mtk: Annotating Predicate Argument Stru(:t, ure
  • 1995
Universii;y of Sheffield: Dcsc,iption of LaSIE system as used fl)r MUC-6
  • Proceedings of the Sixth Mcssag<'~ Understandin 9 Confc/rc'ucc (MUG-6), Morgan I
  • 1995
University of Sheffield: description of the LaSIE system as used for MUC-6
The LaSIE (Large Scale Information Extraction) system has been developed at the University of Sheffield as part of an ongoing research effort into information extraction and, more generally, naturalExpand
\ University ofShe  eld : Description of LaSIE system as used forMUC - 6
  • Oxford AdvancedLearner ' s Dictionary of Current English
  • 1995
\University of Sheeeld: Description of LaSIE system as used for MUC-6
  • Proceedings of the Sixth Message Understanding Conference (MUC-6)
  • 1995
...
1
2
3
4
...