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The annotation or extraction of temporal information from text documents is becoming increasingly important in many natural language processing applications such as text summarization, information retrieval, question answering, etc.. This paper presents an original method for easy recognition of temporal expressions in text documents. The method creates semantically classified temporal patterns, using word co-occurrences obtained from training corpora and a pre-defined seed keywords set, derived from the used language temporal references. A participation on a Portuguese named entity evaluation contest showed promising effectiveness and efficiency results. This approach can be adapted to recognize other type of expressions or languages, within other contexts, by defining the suitable word sets and training corpora. | 221.82 KB | Adobe PDF |
Advisor(s)
Abstract(s)
The annotation or extraction of temporal information from text documents is becoming increasingly important in many natural language processing applications such as text summarization, information retrieval, question answering, etc.. This paper presents an original method for easy recognition of temporal expressions in text documents. The method creates semantically classified temporal patterns, using word co-occurrences obtained from training corpora and a pre-defined seed keywords set, derived from the used language temporal references. A participation on a Portuguese named entity evaluation contest showed promising effectiveness and efficiency results. This approach can be adapted to recognize other type of expressions or languages, within other contexts, by defining the suitable word sets and training corpora.
Description
16th International Symposium on String Processing and Information Retrieval, SPIRE 200925 August 2009 through 27 August 2009 - Code 77796
Keywords
Temporal Expression Training Corpus Annotation Scheme Entity Recognition Text Summarization
Citation
Craveiro, O., Macedo, J., Madeira, H. (2009). Use of Co-occurrences for Temporal Expressions Annotation. In: Karlgren, J., Tarhio, J., Hyyrö, H. (eds) String Processing and Information Retrieval. SPIRE 2009. Lecture Notes in Computer Science, vol 5721. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03784-9_15.
Publisher
Springer
Collections
CC License
Without CC licence