This paper describes the design of a tool for the automatic creation of multi-word lexica that is deployed as a web service and runs on automatically web-crawled data within the framework of the PANACEA platform. The main purpose of our task is to provide a (computationally "light") tool that creates a full high quality lexical resource of multi-word items. Within the platform, this tool is typically inserted in a work flow whose first step is automatic web-crawling. Therefore, the input data of our lexical extractor is intrinsically noisy. The paper evaluates the capacity of the tool to deal with noisy data, and in particular with texts containing a significant amount of duplicated paragraphs. The accuracy of the extraction of multi-word expressions from the original crawled corpus is compared to the accuracy of the extraction from a later "de-duplicated" version of the corpus. The paper shows how our method can extract with sufficiently good precision also from the original, noisy crawled data. The output of our tool is a multi-word lexicon formatted and encoded in XML according to the Lexical Mark-up Framework.
Automatic Creation of Quality Multi-Word Lexica from Noisy Text Data
Francesca Frontini;Valeria Quochi;
2012
Abstract
This paper describes the design of a tool for the automatic creation of multi-word lexica that is deployed as a web service and runs on automatically web-crawled data within the framework of the PANACEA platform. The main purpose of our task is to provide a (computationally "light") tool that creates a full high quality lexical resource of multi-word items. Within the platform, this tool is typically inserted in a work flow whose first step is automatic web-crawling. Therefore, the input data of our lexical extractor is intrinsically noisy. The paper evaluates the capacity of the tool to deal with noisy data, and in particular with texts containing a significant amount of duplicated paragraphs. The accuracy of the extraction of multi-word expressions from the original crawled corpus is compared to the accuracy of the extraction from a later "de-duplicated" version of the corpus. The paper shows how our method can extract with sufficiently good precision also from the original, noisy crawled data. The output of our tool is a multi-word lexicon formatted and encoded in XML according to the Lexical Mark-up Framework.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.